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Creating Videos with OpenShot Video Editor: A Comprehensive Tutorial

Getting Started with OpenShot

OpenShot Video Editor, a free-to-use open-source product that allows you to make your own videos quickly and easily, even if you're a beginner. It is available for all major platforms, including Windows, Mac, and Linux. OpenShot boasts an intuitive user interface with the Project Files panel on the left, the Video Preview on the right, and the project Timeline at the bottom. Let's explore how to create a video with it!

OpenShot Video Editor

Initially, your project is empty, and you can add your media files either by using the Import Files button or by dragging and dropping them into the Project Files panel. Your files are organized by type (video, audio, or image) and can be placed on the Timeline as clips in different Tracks, which are stacked layers composing your final video. You have five default Tracks, but you can add or remove them as needed.

These Tracks accommodate both visual and audio content, displaying file names and thumbnails. You can also view audio waveforms by right-clicking on a clip and selecting Display, Show Waveform, which reveals the volume envelope over time. To navigate the Timeline, use Ctrl/Cmd + mouse wheel to zoom in and out around the red marker and Alt/Option + mouse wheel to move through time.

For detailed content review, use the Video Preview on the right, which shows the Timeline content under the red playhead. You can replace the playhead and drag it through time to view different frames. To playback with audio, use the player below the Preview. Adjust preview properties, like size and frame rate, by going to Choose Profile at the top.

Editing Timeline Clips and working with Keyframes

Now, let's delve into editing Timeline clips. You can click on a clip to select it and move it within the same Track or to a different one, allowing for overlapping clips and controlling their visibility order. Adjust clip duration by clicking and dragging its edges, which also trims video and audio content accordingly.

Copying and pasting clips is as simple as Ctrl/Cmd + C and Ctrl/Cmd + V. The pasted clip is inserted after the red marker in time. To delete a selected clip, press the Backspace key, and undo with Ctrl/Cmd + Z.

Right-clicking on a clip and selecting Properties provides a list of adjustable properties such as cropping, positioning, rotating, scaling, and shearing. You can use Scale to automatically remove black bars by stretching or cropping the clip, and Volume to adjust the audio level. Edit these values by dragging or double-clicking and typing directly, applying with the Enter key.

Some properties change over time, indicated by a green color and the creation of keyframes. Keyframes are markers that save property values at specific instants. Adding multiple keyframes creates transitions between them. Each clip has one default keyframe at the beginning, storing default property values. Placing the playhead at a different time and changing a property creates a new keyframe, enabling transitions.

To modify keyframes, right-click on the keyframe of interest to adjust the transition envelope or remove the keyframe. If you prefer not to use keyframes and transitions, place the playhead on the default keyframe and edit the property value directly.

Additionally, you can apply quick animations, adjust video and audio speed rates under Time, and perform basic clip editing with Transform by right-clicking on a clip. To separate audio from video frames, use Separate Audio, making them independent. To split a clip, enable the Razor tool and click on the clip directly.

OpenShot offers impressive visual and audio transitions. Right-click on a clip to apply Fade transitions that change transparency over time or Volume transitions to adjust audio levels. Explore more visual transitions in the Transitions panel, where you can drag and drop them onto the timeline to create blue transition clips. By default, these apply fade-in transitions, but you can reverse them or adjust their length for varying speeds.

Find various visual effects in the Effects panel, drag and drop them onto clips, and adjust their values while previewing in the Properties panel. To remove an effect, right-click on it. Create titles by navigating to Title, selecting a text template, and customizing its appearance, including font, style, content, and colors. Import titles into the Timeline and edit them like other clips. For advanced text, use Inkscape or Blender if installed on your computer.

To save your project, use Ctrl/Cmd + S, saving it as an OpenShot project (.osp). To export your final video, click Export Video, set the name, destination folder, profile, video format, resolution, aspect ratio, and quality. In the Advanced tab, you can fine-tune export settings, including video and audio options, the last frame, and detailed properties.

Thank you for watching this tutorial! Check out our YouTube channel to discover more fantastic free software!

Optimizing Your Vertical Video Editing Process in OpenShot - A Comprehensive Tutorial

Introduction

In this OpenShot tutorial, I will guide you through the process of editing a sequence of vertical video clips. Whether you're a beginner or have some editing experience, this tutorial will help you get started.

OpenShot Video Editor

Step 1: Adjusting OpenShot Settings

1.1 Default Settings: When you open OpenShot, it defaults to a 16:9 wide-angle aspect ratio. We'll make some adjustments.

1.2 Changing Default Profile: Select 'Edit' > 'Preferences' and change the default profile to 'HD Vertical 1080p 30 frames per second' to match vertical video.

1.3 Increasing Cache: Increase the cache size to at least 10,000 megabytes (MB) to improve performance.

Step 2: Importing Video Clips

2.1 Drag and Drop: Open your file browser, select the vertical video clips you want, and drag them into OpenShot's panel.

2.2 Panel Adjustment: Adjust panel sizes to your preference.

Step 3: Overcoming OpenShot's Lag Issue

3.1 The Lag Problem: OpenShot can be laggy, especially with larger videos. To mitigate this, follow these steps.

3.2 Force Cache Adjustment: To change the cache size, go to 'Edit' > 'Preferences,' insert cache, and increase or decrease it by one (e.g., 19,999 MB).

3.3 Playback: Double-click the fast-forward button to play and wait for the blue line to fill completely.

Step 4: Cutting and Editing Video Clips

4.1 Markers: Place markers at the points where you want to cut your video.

4.2 Slicing: Right-click on a marker, choose 'Slice All,' and select which side to keep (left or right).

4.3 Repeat: Continue this process for each section you want to cut.

Step 5: Arranging and Final Playback

5.1 Arrange Clips: Drag the edited video clips together to ensure they snap into place.

5.2 Playback: Play the edited video; it should be smoother now that the cache has processed.

Step 6: Exporting Your Edited Video

6.1 Exporting: Click the 'Export Video' button.

6.2 File Naming: Give your video a title.

6.3 Choose Destination: Select where you want to save your video.

6.4 Export: Click 'Export Video' to begin rendering your edited vertical video.

Conclusion

You've successfully edited a vertical video using OpenShot. Your edited video is ready to be shared on your favorite media platform. Thank you for watching this tutorial! Cheers!

Python Scripts for Automated Youtube Videos Generation

Youtube Video Screenshot Capture at Particular Time

To take a screenshot of a YouTube video at a particular minute or second input by the user, you can use Python along with libraries like selenium to interact with the web page and Pillow (PIL) to capture and save the screenshot. Make sure you have these libraries installed. You'll also need a web driver for Selenium (e.g., ChromeDriver).

Here's a Python script to achieve this:

import time

from selenium import webdriver

from selenium.webdriver.common.by import By

from PIL import Image

# Function to take a screenshot of a YouTube video

def capture_youtube_screenshot(video_url, time_in_seconds, output_file):

    # Initialize the Chrome web driver

    driver = webdriver.Chrome(executable_path='path/to/chromedriver')

    try:

        # Open the YouTube video in the web driver

        driver.get(video_url)

        # Convert time to minutes and seconds

        minutes = time_in_seconds // 60

        seconds = time_in_seconds % 60

        # Seek to the specified time in the video

        seek_bar = driver.find_element(By.CSS_SELECTOR, '.ytp-progress-bar-container')

        driver.execute_script(f"arguments[0].style.width = '{(time_in_seconds / (duration + 1)) * 100}%';", seek_bar)

        # Wait for the video to load and seek to the specified time

        time.sleep(5)  # Adjust this delay if needed

        # Take a screenshot

        screenshot = driver.get_screenshot_as_png()

        # Save the screenshot as an image file

        with open(output_file, 'wb') as f:

            f.write(screenshot)

        print(f'Screenshot saved to {output_file}')

    finally:

        # Close the web driver

        driver.quit()

if __name__ == "__main__":

    video_url = input("Enter the YouTube video URL: ")

    time_in_seconds = int(input("Enter the time in seconds to capture the screenshot: "))

    output_file = input("Enter the output file name (e.g., screenshot.png): ")

    # Call the function to capture the screenshot

    capture_youtube_screenshot(video_url, time_in_seconds, output_file)

Make sure to replace 'path/to/chromedriver' with the actual path to the ChromeDriver executable on your system. You can download ChromeDriver from the official website: https://sites.google.com/chromium.org/driver/

This code will open the specified YouTube video, seek to the specified time, take a screenshot, and save it as the specified output file.

Python Script for Making Videos from Multiple Videos

To create a Python script that allows you to input multiple video names, start and end times for trimming, and then compile the trimmed videos into a new one, you can use the moviepy library. Make sure you have this library installed:

from moviepy.video.io.ffmpeg_tools import ffmpeg_extract_subclip

from moviepy.editor import VideoFileClip

def trim_video(input_file, output_file, start_time, end_time):

    # Convert start_time and end_time to milliseconds

    start_time_ms = start_time * 1000

    end_time_ms = end_time * 1000

    # Trim the video using ffmpeg

    ffmpeg_extract_subclip(input_file, start_time_ms, end_time_ms, targetname=output_file)

def compile_videos(input_video_list, output_file):

    video_clips = []

    

    # Load each input video and add it to the list

    for video_file in input_video_list:

        video_clip = VideoFileClip(video_file)

        video_clips.append(video_clip)

    

    # Concatenate the video clips to create the final video

    final_video = VideoFileClip.empty()

    for clip in video_clips:

        final_video = final_video.append(clip)

    

    # Write the final video to the output file

    final_video.write_videofile(output_file, codec='libx264')

    print(f'Compiled video saved as {output_file}')

if __name__ == "__main__":

    input_video_list = []

    num_videos = int(input("Enter the number of videos to compile: "))

    for i in range(num_videos):

        video_name = input(f"Enter the name of video {i + 1}: ")

        input_video_list.append(video_name)

    start_time = float(input("Enter the start time (in seconds) for trimming: "))

    end_time = float(input("Enter the end time (in seconds) for trimming: "))

    output_file = input("Enter the output file name (e.g., compiled_video.mp4): ")

    # Trim each input video and compile them into a single video

    trimmed_videos = []

    for i, video_file in enumerate(input_video_list):

        trimmed_file = f"trimmed_video_{i}.mp4"

        trim_video(video_file, trimmed_file, start_time, end_time)

        trimmed_videos.append(trimmed_file)

    compile_videos(trimmed_videos, output_file)

This script allows you to input the names of multiple videos, specify the start and end times for trimming, and then compiles the trimmed videos into a single output file.

Unlocking the Power of Modal: Simplified Cloud Computing for Developers

What is Modal.com and How does it works?

Modal offers end-to-end cloud compute services, making it easy for users to run code in the cloud without needing to set up complex infrastructure. Here are some key points about Modal based on the information provided:

Ease of Use: Modal allows users to run their code in the cloud within seconds, eliminating the need to install Docker, set up Kubernetes clusters, or have an AWS account.

High Performance: Modal is built from scratch for high performance, with a container runtime written in Rust designed for modern use cases.

Infinite Use Cases: Modal supports a wide range of use cases, including model inference, job queues, large-scale parallelism, web apps, and cron jobs.

Seamless Deployment: Users can deploy code from a local machine to the cloud with just two additional lines of code, enabling a seamless development and deployment process.

Self-Provisioning Runtime: Modal allows users to define their environment in code, including Python libraries, binary dependencies, and datasets, without the need to install Docker. Modal will build the necessary environment for you.

Scalability: Modal supports a variety of applications and offers flexibility in compute resources, allowing users to deploy and scale anything from web scraping to 3D rendering.

Pay-as-You-Go: Modal charges users based on the time their code runs in the cloud, with the ability to scale resources to zero by default.

Scheduled Tasks: Modal supports scheduled tasks, such as cron jobs, and provides an instant feedback loop for running code in the cloud.

Community Support: Modal has garnered positive feedback from the developer community for its ease of use and powerful abstractions.

Use Cases: Modal offers various use cases, including machine learning model training, real-time object detection, podcast transcriptions, dataset analysis, question-answering, and more.

Overall, Modal appears to be a platform designed to simplify cloud computing tasks and accelerate the development and deployment of cloud-based applications for developers and engineering teams.

Pricing Model

To compute the costs for each plan, we need to consider the provided information about the cost per second or per hour for CPU, GPU, and memory, as well as the included credits and variable costs for each plan. We'll calculate the costs for each plan based on the given information.

Modal Computation Cost Per Hour

Starter Plan:

- Included credits: $10/month

- CPU concurrency: 1000

- GPU concurrency: 10

Let's calculate the costs:

1. CPU cost per hour (assuming 1 core):

   - $0.192/core/hour

   - 1 core

   - 1 hour

   - Total CPU cost = $0.192

2. GPU cost per hour (assuming Nvidia A100, 40 GB):

   - $3.73/hour

   - 1 GPU

   - 1 hour

   - Total GPU cost = $3.73

3. Total cost for included credits and CPU/GPU usage:

   - Included credits: $10/month

   - Total cost = Included credits - (CPU cost + GPU cost)

   - Total cost = $10 - ($0.192 + $3.73) = $10 - $3.922 = $6.078/month

Organization Plan:

- Included credits: $30/month

- CPU concurrency: Unlimited

- GPU concurrency: 30

Let's calculate the costs:

1. CPU cost per hour (assuming 1 core):

   - $0.192/core/hour

   - Unlimited CPU concurrency

   - 1 hour

   - Total CPU cost = $0.192 x 1 x 1 = $0.192/hour

2. GPU cost per hour (assuming Nvidia A100, 40 GB):

   - $3.73/hour

   - 30 GPUs (as per plan)

   - 1 hour

   - Total GPU cost = $3.73 x 30 x 1 = $111.90/hour

3. Total cost for included credits and CPU/GPU usage:

   - Included credits: $30/month

   - Total cost = Included credits - (CPU cost + GPU cost)

   - Total cost = $30 - ($0.192/hour + $111.90/hour)

   - Total cost = $30 - $112.092 = -$82.092/month (This plan appears to be free, assuming the credits cover the usage)

Enterprise Plan:

- Included credits: Custom

- CPU and GPU concurrency: Custom

Since the Enterprise Plan has custom pricing and resource allocation, we can't calculate the cost without specific details about the number of seats, CPU/GPU usage, and included credits.

Please note that the calculations assume constant usage over the entire month. In reality, usage may vary, and the cost will depend on the actual resource utilization.

For accurate cost estimates, you should contact the service provider to get detailed pricing based on your specific requirements.

Less Competition and High Paying ChatGPT development Jobs

ChatGPT Development Skills that will Pay you Very Well

In the rapidly evolving landscape of artificial intelligence, the demand for skilled professionals who can harness the power of advanced language models like ChatGPT is surging. With the advent of AI-driven technologies, a new realm of employment opportunities has emerged, offering lucrative positions that promise both less competition and high earning potential. As businesses seek innovative solutions to enhance customer engagement, automate processes, and create cutting-edge applications, the market for ChatGPT development jobs is witnessing remarkable growth. This article delves into the realm of ChatGPT development, exploring the diverse job prospects, the skills that are in demand, and the exciting potential that lies ahead for those seeking to make their mark in this dynamic field.

High-Paying and less competition ChatGPT Jobs

Learn to Create Online Course for ChatGPT Prompts

It seems like you've shared a detailed description of a job opportunity with LearningWhilePracticing for a prompt engineer or GenAI expert to create an online course titled 'ChatGPT Unleashed: Mastering Conversational AI.' The course focuses on teaching students about Conversational AI using the ChatGPT model through practical examples and a 'learning by doing' methodology. 

The job description highlights the following key points:

1. Company Background: LearningWhilePracticing is an established online course provider with a strong community of learners. The company offers on-demand video tutorials in various fields, such as programming, office applications, music production, and photo/video editing.

2. Job Role: The prompt engineer or GenAI expert will be responsible for creating a comprehensive online course on Conversational AI using ChatGPT. The course will be divided into three milestone segments, each consisting of four main sections.

3. Teaching Approach: LearningWhilePracticing emphasizes a 'learning by doing' methodology, allowing students to engage with the software and practical examples right from the beginning. This approach aims to ensure a deeper understanding and practical application of the concepts being taught.

4. Requirements: The job requires recording high-quality on-screen videos of teaching, using self-generated examples and content. The videos will be edited by LearningWhilePracticing. Clear audio quality, excellent English proficiency, and good pronunciation are essential. Applicants will need to provide a short example, and intellectual property rights will be retained by the company with a signed NDA.

5. Opportunity: The course created by the chosen expert will be exposed to thousands of students, providing an opportunity to gain recognition and make a name in the field.

6. Equal Opportunity: LearningWhilePracticing is an equal opportunity company.

7. Table of Contents: The detailed table of contents for the course is provided in an attached file.

Simple Steps to do this Job

Certainly! Here are the steps you can follow to successfully complete the job of creating the online course "ChatGPT Unleashed: Mastering Conversational AI" for LearningWhilePracticing:

1. Understand the Course Objectives:

   - Review the provided table of contents and the overall course objectives to gain a clear understanding of what topics and skills need to be covered.

2. Research and Preparation:

   - Familiarize yourself with ChatGPT and Conversational AI concepts through research and studying available resources.

   - Identify key concepts, use cases, and practical examples that will be covered in each milestone segment.

3. Content Creation:

   - Prepare scripts or outlines for each section of the course based on the provided table of contents.

   - Generate relevant Word files, code examples, and practical scenarios that demonstrate Conversational AI concepts using ChatGPT.

   - Ensure that the content follows a logical flow and is suitable for a 'learning by doing' approach.

4. Video Recording Setup:

   - Set up your recording environment with proper lighting and a clutter-free background.

   - Use a high-quality microphone and recording software (such as OBS) to ensure clear audio and video.

5. Video Recording:

   - Record on-screen videos of yourself teaching the content using the Word files and examples you've generated.

   - Follow the script or outline, explaining concepts clearly and step by step.

   - Ensure that your pace is comfortable for learners to follow and that you maintain engaging and enthusiastic delivery.

6. Video Quality and Audio Check:

   - Review the recorded videos to ensure they are of the highest quality in terms of both video resolution and audio clarity.

   - Address any background noise, distractions, or audio issues before finalizing the videos.

7. Editing and Post-Production:

   - Deliver the raw video files to LearningWhilePracticing for editing.

   - The editing process may involve adding graphics, subtitles, transitions, and other enhancements to improve the overall quality of the videos.

8. Review and Approval:

   - Review the edited videos to ensure they accurately represent your teaching and meet the course objectives.

   - Make any necessary revisions based on feedback from LearningWhilePracticing.

9. Finalization and Delivery:

   - Provide the finalized video content to LearningWhilePracticing for integration into their platform.

   - Ensure that all video files, supplementary materials, and documentation are organized and submitted as required.

10. Short Example Submission:

   - If requested, provide a short example of your teaching style and content delivery to demonstrate your suitability for the role.

11. Intellectual Property and NDA:

   - Be prepared to sign a non-disclosure agreement (NDA) and understand the company's terms regarding intellectual property rights.

12. Engage with the Learning Community:

   - Consider participating in discussions, Q&A sessions, and providing additional support to students who enroll in the course.

13. Continuous Improvement:

   - Stay open to feedback and suggestions from both learners and LearningWhilePracticing to enhance the course content over time.

By following these steps, you'll be able to effectively create the "ChatGPT Unleashed: Mastering Conversational AI" course while meeting the expectations of LearningWhilePracticing and delivering an exceptional learning experience for the students.

Chatbot development using ChatGPT and RASA

Here are some technical details on the libraries and methods you can use for each of the points you mentioned:

1. Accuracy of Responses:

Libraries: RASA NLU and RASA Core

Method: Train your chatbot's NLU model with a larger dataset and fine-tune it for better intent recognition and entity extraction. Experiment with different algorithms and pipeline configurations to find the best accuracy.

2. Multilingual Support:

Libraries: RASA NLU, RASA Core, spaCy (for language tokenization)

Method: Create a separate pipeline for Hindi language processing in RASA NLU. Translate and augment your training data to include Hindi examples. Use pre-trained word embeddings like fastText for Hindi. Configure a Hindi language model for response generation.

3. Connecting Chatbot Model with UI:

Libraries: RASA Core, RASA SDK

Method: Deploy your RASA Core model and custom actions using the RASA SDK. Set up a communication channel (e.g., REST API) to handle messages from the UI and send responses back.

4. Connecting DBMS Tools:

Libraries: RASA Core, RASA SDK, SQLalchemy (for database interaction)

Method: Create custom actions in the RASA SDK to fetch data from your chosen DBMS. Use SQLalchemy to interact with the database. Respond to user queries with data retrieved from the DBMS.

5. Improving RASA Functionality:

Libraries: RASA NLU, RASA Core, spaCy, transformers

Method:

Customize RASA NLU components: Experiment with different tokenizers, entity extractors, and featurizers for better understanding of specialized terms.

Fine-tune transformers: Use pre-trained transformer models like BERT or GPT for improved language understanding.

Combine external NLP tools: Integrate spaCy for advanced text processing and named entity recognition.

6. Adding Research Elements:

Libraries: PyTorch, TensorFlow, OpenAI's GPT models

Method: Depending on your research element, you might:

Experiment with reinforcement learning algorithms for dialogue management, using frameworks like TensorFlow or PyTorch.

Incorporate sentiment analysis using pre-trained models to gauge customer satisfaction.

Integrate OpenAI's GPT models to enhance the chatbot's ability to generate natural language responses.

Remember that the choice of libraries and methods depends on your specific project requirements and your familiarity with these tools. Regular testing and experimentation will help you refine your approach and achieve your goals. Be prepared to iterate and fine-tune your implementation based on user feedback and performance metrics.

Content Creation Using Generative AI

Certainly! Here's a concise explanation of the task, followed by the technical steps and methods to achieve it:

Explanation:

You are seeking a digital content creator expert who can produce videos using AI tools such as ChatGPT, InVideo, Mid Journey, Stability, InShot, and more. The goal is to create engaging videos from text input using AI-powered tools without any manual editing. These videos can involve various creative transformations, such as converting footage to anime or giving it a space-themed look. The process requires utilizing AI algorithms and internet resources to generate visually appealing content.

Technical Steps and Methods:

1. Collect Resources:

   - Gather relevant video footages and assets that you have for editing, which may include high-definition camera footages.

2. Choose AI Tools:

   - Select appropriate AI tools such as ChatGPT, InVideo, Mid Journey, Stability, InShot, etc., depending on the specific effects or transformations you want to achieve.

3. Generating Ideas:

   - Use ChatGPT or similar AI tools to generate creative ideas based on the provided text input. These ideas will guide the transformation of your video content.

4. AI Transformation:

   - Depending on the AI tools chosen, apply transformations to your video content:

     - InVideo: Use AI-powered templates, effects, and transitions to enhance the footage.

     - Mid Journey, Stability: Utilize AI-based video enhancement techniques to stabilize footage, enhance colors, or add effects.

     - InShot: Apply AI filters, effects, and adjustments to enhance video quality.

5. Automated Editing:

   - Implement the transformations and effects generated by the AI tools onto the video footages without manual intervention. This can involve scripting and automation to apply the effects consistently.

6. Artistic Themes:

   - Based on your text input and creative ideas, tailor the videos to specific themes, such as anime or space themes, by applying relevant filters, overlays, and effects.

7. Quality Control:

   - Review the generated videos to ensure that the AI-generated effects align with the intended creative vision and desired output.

8. Regular Content Creation:

   - Create a process or script that automates the generation of videos from your provided text input on a daily basis.

9. Distribution:

   - After generating the videos, distribute them on platforms like Instagram Reels and YouTube Shorts as per your content strategy.

Important Considerations:

- It's essential to have experience with the chosen AI tools to effectively utilize their capabilities.

- Automated editing and transformations might not always be perfect, so occasional manual adjustments might be necessary for optimal results.

- Ensure that the content aligns with copyright and fair use policies, especially when using AI-generated content.

By following these technical steps and leveraging AI tools effectively, you can create engaging videos with various effects and transformations for platforms like Instagram Reels and YouTube Shorts.

AI-Driven Social Media Content Creator for News Summaries

An AI-savvy individual to create captivating social media content by abstracting news articles. This person should have AI and NLP expertise, along with strong writing skills. Their role involves summarizing news articles for social media in a concise, engaging manner. They'll use Google Sheets to track references via hyperlinks and receive PDF articles to process using AI and Google apps. Turnaround time for each article is expected to be under 6 hours once the PDF is received. 

METHODOLOGY

Certainly! Here are the technical steps and recommended libraries you can use for abstracting news articles and creating engaging content using AI:

Text Extraction from PDF:

Libraries: PyPDF2, pdfplumber

Extract text from the provided PDF articles using Python libraries like PyPDF2 or pdfplumber.

Natural Language Processing (NLP):

Libraries: NLTK, spaCy, BERT, GPT-3

Process the extracted text using NLP libraries such as NLTK or spaCy for tasks like tokenization, sentence segmentation, and named entity recognition.

Optionally, you can leverage more advanced models like BERT or GPT-3 for improved understanding of context and semantics.

Summarization:

Libraries: transformers, gensim, sumy

Use library functions to create abstractive or extractive summaries of the news articles. Libraries like transformers (using models like BERT) or gensim can help generate coherent summaries.

Alternatively, you can use the sumy library for extractive summarization.

Content Generation:

Libraries: GPT-3, OpenAI API, T5

Utilize models like GPT-3 or T5 for generating engaging content based on the summarized text. These models can assist in crafting social media-friendly content.

Google Sheets Integration:

Libraries: Google Sheets API (Python library)

Set up the Google Sheets API to interact with Google Sheets from your Python script. Use it to create a worksheet that tracks references, people, property, firms, and news articles.

Automation and Workflow:

Implement a script that, upon receiving a PDF article, automates the entire process:

Extract text using a chosen library.

Apply NLP processing for better understanding.

Generate summaries using the preferred summarization library.

Generate engaging content using AI models.

Populate Google Sheets with relevant data.

Turnaround Time Management:

Set up a system to notify and track the progress of each PDF article's processing time to ensure it meets the expected turnaround time of under 6 hours.

By following these technical steps and leveraging the mentioned libraries, you can efficiently abstract news articles and create engaging content for social media platforms using AI.

Create an Engaging Sales Copy for Any Leisure Audience

Work Description:

Content Creation: Craft compelling and authentic email and ad copy targeted at golf companies using ChatGPT. The content should resonate with golf enthusiasts and reflect the language and culture of the game.

Visual Selection: Choose relevant images that align with our social media ads and emails, enhancing the golf theme. If needed, request specific images that complement the content.

Collaboration: Collaborate with team members by sharing your work for review and integration. Your role is crucial in maintaining a collaborative environment across different departments.

Required Skills:

Golf Knowledge: Deep understanding of golf, encompassing rules, terminology, and the golfing culture.

ChatGPT Expertise: Proficiency in utilizing ChatGPT for generating content tailored to golfing audiences.

Google Docs/Sheets: Skillful use of Google Docs and Sheets for content organization and collaborative work.

Slack Familiarity: Familiarity with Slack for effective communication within the team.

Qualifications:

Effective Writing: Strong writing skills enabling you to capture the essence of golf in your copy.

Adaptability: Ability to work efficiently in a dynamic environment and adhere to deadlines.

If you're an enthusiastic golfer who understands the intricacies of the sport and possesses the necessary technical skills, this role offers the chance to contribute your golf expertise and creative talents to our team's golf-oriented projects.

ChatGPT Prompts to get your desired Output

Certainly! Here are some effective prompts you can use for the ChatGPT job description:

1. Crafting Email and Ad Copy:

   - "Generate engaging email and ad copy targeted at golf companies, showcasing our products/services in a way that resonates with avid golfers and captures the essence of the game."

2. Reflecting Golf Language:

   - "Create authentic content that speaks the unique lingo of golf, infusing the copy with terminology, passion, and culture that golf enthusiasts will instantly connect with."

3. Image Selection and Enhancement:

   - "Suggest visually appealing images that align seamlessly with our social media ads and email content, elevating the golf theme and enhancing the overall impact."

4. Collaborative Environment:

   - "Contribute to a collaborative ecosystem by sharing your copy for review and integration with other team members across departments, ensuring a cohesive and engaging final output."

5. Showcasing Golf Knowledge:

   - "Utilize your in-depth knowledge of golf, including its rules, terminology, and cultural nuances, to craft copy that resonates with both dedicated golfers and industry professionals."

6. Incorporating ChatGPT Expertise:

   - "Leverage your experience in effectively using ChatGPT for content creation, shaping golf-specific copy that captures attention and fosters engagement."

7. Google Docs and Sheets Proficiency:

   - "Organize your golf-oriented content efficiently using Google Docs and Sheets, streamlining collaboration and ensuring seamless content creation."

8. Seamless Slack Communication:

   - "Utilize Slack as a communication tool to effectively coordinate with team members, facilitating smooth exchange of ideas and content updates."

9. Effective Writing Skills:

   - "Employ your strong writing skills to encapsulate the essence of golf within your copy, creating persuasive and relatable content that aligns with our objectives."

10. Meeting Deadlines in a Dynamic Environment:

    - "Demonstrate your ability to thrive in a fast-paced environment by consistently delivering high-quality content within deadlines, ensuring the timely execution of our projects."

Feel free to customize these prompts to align with the specific details and expectations of the ChatGPT job description.

FINAL WORDS

In conclusion, the rise of ChatGPT and similar language models has ushered in a new era of job opportunities that offer less competition and high earning potential. From crafting compelling copy to engineering advanced integrations, the breadth of ChatGPT development jobs is vast and ever-expanding. As AI technology continues to evolve and integrate into various industries, professionals skilled in harnessing the capabilities of ChatGPT are well-positioned to thrive in an increasingly AI-driven world. By staying updated with the latest advancements, honing relevant skills, and embracing the innovative possibilities that ChatGPT brings, aspiring developers can carve out fulfilling careers that combine creativity, technology, and the potential for substantial financial rewards.

Summary - Current ChatGPT Development Jobs:

The world of ChatGPT development presents a range of job opportunities that cater to different skill sets and interests. Some of the prominent roles include:

1. Content Creation and Copywriting:Businesses require skilled content creators who can leverage ChatGPT to generate engaging blog posts, articles, marketing copies, and social media content.

2. Automated Customer Support:As companies look to streamline customer interactions, ChatGPT developers are needed to build AI-powered chatbots that provide efficient and personalized customer support.

3. Integration Specialists:Professionals proficient in integrating ChatGPT with various platforms, applications, and websites are in demand to enhance user experiences and automate processes.

4. Educational Content Development:The education sector seeks ChatGPT developers to create interactive and personalized learning materials, benefiting students and educators alike.

5. Creative Writing and Storytelling:ChatGPT is used to craft interactive narratives, game dialogues, and immersive storytelling experiences, opening avenues for creative writers in the gaming and entertainment industry.

6. Research and Innovation:Researchers and developers collaborate to push the boundaries of ChatGPT's capabilities, working on cutting-edge projects in natural language processing and AI advancements.

7. Social Media Management:Social media managers utilize ChatGPT to schedule posts, engage with followers, and develop strategic content plans.

NOTE

These roles, among others, demonstrate the breadth of opportunities in ChatGPT development. With the field constantly evolving, professionals who combine technical expertise with creativity will find themselves well-positioned in the landscape of less competition and high-paying AI jobs.

Write the Best Proposal for AI-driven development Jobs in Python

Write the Best Proposal for AI-driven development Jobs

Crafting an effective proposal is much more than just putting pen to paper; it's about persuading your audience that you are the right person for the job, project, or partnership. Whether you're a seasoned freelancer, a corporate professional, or a passionate hobbyist, your proposal serves as a formal introduction to your skills and a persuasive pitch for why you should be chosen. A well-written proposal can open doors to new opportunities and cement your reputation as a go-to expert in your field. In this article, you'll learn the art and science of crafting compelling proposals that captivate your audience from the first line to the last.

Comprehensive OCR Proposal: Catering to Beginner to Complex OCR Development

Prepared by: [Your Name]

Date: [Date]

Introduction:

I am thrilled to present this comprehensive proposal that outlines my expertise and commitment to delivering exceptional OCR (Optical Character Recognition) solutions using Python. From beginner-level projects to complex OCR development, my technical proficiency and dedication make me a valuable partner for your OCR needs. This proposal provides a holistic framework that caters to a wide spectrum of OCR requirements.

Scope and Approach:

My approach to OCR projects is rooted in Python's capabilities and its powerful libraries for image processing and text extraction. I specialize in delivering versatile solutions that encompass both simple text extraction tasks and intricate document processing needs. Whether it's basic character recognition or sophisticated layout analysis, I am well-equipped to address your project's unique challenges.

Key Strengths:

1. Python Proficiency: I possess an in-depth understanding of Python and its libraries, such as OpenCV and Tesseract, to execute accurate and efficient OCR tasks.

2. Image Preprocessing: I excel at image preprocessing techniques, ensuring optimal input for OCR algorithms by enhancing image quality, noise reduction, and contrast adjustment.

3. Text Extraction: My expertise includes extracting text from images, scanned documents, and PDFs with precise character recognition and format retention.

4. Layout Analysis: I am adept at handling complex documents with layout analysis, preserving hierarchical structures, tables, and formatting.

5. Machine Learning Integration: For complex OCR tasks, I can leverage machine learning models for improved accuracy, such as training custom models using TensorFlow or PyTorch.

6. Data Validation and Cleansing: I ensure the accuracy of extracted text through data validation, cleansing, and post-processing techniques.

7. Custom Solutions: My experience extends to developing custom OCR pipelines, integrating OCR into existing systems, and automating document workflows.

Project Scenarios:

From beginners seeking basic OCR capabilities to enterprises with complex document processing needs, I can tailor solutions to various scenarios:

1. Beginner-Level OCR:

   - Implement basic OCR capabilities using Tesseract or other libraries.

   - Extract text from simple images and scanned documents.

   - Enhance text extraction accuracy through preprocessing techniques.

2. Intermediate-Level OCR:

   - Process documents with complex layouts, headers, footers, and tables.

   - Integrate machine learning models for improved character recognition.

   - Develop scripts for batch processing of multiple documents.

3. Advanced-Level OCR:

   - Create custom OCR models for domain-specific recognition tasks.

   - Build OCR pipelines for automated data extraction from diverse document types.

   - Implement intelligent document sorting and classification using OCR metadata.

Conclusion:

My versatile skill set and dedication to delivering high-quality OCR solutions position me as an ideal partner for projects spanning from beginner to advanced levels. I am excited about the opportunity to collaborate with you and provide OCR solutions that align with your unique needs.

Thank you for considering my proposal. I am eager to contribute my expertise to your OCR projects and help you achieve outstanding results.

Sincerely,

[Your Name]

[Your Contact Information]

Comprehensive NLP Proposal: Addressing Beginner to Complex NLP Development

Prepared by: [Your Name]

Date: [Date]

Introduction:

I am delighted to present a comprehensive proposal that outlines my expertise and dedication in delivering exceptional Natural Language Processing (NLP) solutions using Python. From beginner-level tasks to complex NLP development, my technical proficiency and commitment to excellence make me a valuable partner for your NLP projects. This proposal provides a holistic framework that caters to a wide spectrum of NLP requirements.

Scope and Approach:

My approach to NLP projects is grounded in Python's capabilities and its rich ecosystem of libraries for text analysis, machine learning, and deep learning. I specialize in providing versatile solutions that encompass both fundamental text processing tasks and intricate language understanding challenges. Whether it's basic sentiment analysis or advanced language generation, I am well-equipped to address your project's unique complexities.

Key Strengths:

1. Python Proficiency: I possess a deep understanding of Python and its libraries, such as NLTK, spaCy, and TensorFlow, enabling me to create effective NLP solutions.

2. Text Preprocessing: I excel at applying preprocessing techniques to clean and tokenize text, optimizing input for NLP algorithms.

3. Text Classification: My expertise includes developing models for text classification tasks like sentiment analysis, topic categorization, and intent recognition.

4. Named Entity Recognition (NER): I am adept at identifying entities such as names, dates, and locations within text, crucial for information extraction.

5. Sequence-to-Sequence Models: I can develop sequence-to-sequence models for tasks like machine translation, summarization, and dialogue generation.

6. Transfer Learning and Embeddings: I leverage pre-trained embeddings and transfer learning to enhance model performance on various NLP tasks.

7. Custom Solutions: My experience extends to building custom NLP pipelines, integrating NLP into applications, and addressing domain-specific language challenges.

Project Scenarios:

From beginners seeking foundational NLP capabilities to enterprises requiring advanced language understanding, I can tailor solutions to various scenarios:

1. Beginner-Level NLP:

   - Implement basic text preprocessing techniques and tokenization.

   - Develop sentiment analysis models to determine sentiment polarity.

   - Perform basic frequency analysis and word cloud visualizations.

2. Intermediate-Level NLP:

   - Build text classification models for topic categorization.

   - Develop Named Entity Recognition models to identify entities in text.

   - Create language models for text completion and generation.

3. Advanced-Level NLP:

   - Implement sequence-to-sequence models for machine translation.

   - Develop advanced chatbots using natural language understanding and generation.

   - Perform deep sentiment analysis with context understanding.

Conclusion:

My versatile skill set and dedication to delivering high-quality NLP solutions position me as an ideal partner for projects ranging from beginner to advanced levels. I am excited about the prospect of collaborating with you to provide NLP solutions that align with your unique needs.

Thank you for considering my proposal. I look forward to the opportunity to contribute my expertise to your NLP projects and help you achieve exceptional results.

Sincerely,

[Your Name]

[Your Contact Information]

General Proposal Template for Various Projects

Prepared by: [Your Name]

Date: [Date]

Introduction:

I am pleased to submit this versatile proposal, showcasing my expertise as a Python developer capable of delivering exceptional solutions across a wide range of projects. With a deep understanding of programming principles, problem-solving, and a commitment to excellence, I am well-prepared to address your unique project requirements. This proposal serves as an overarching framework for collaborations in diverse domains.

Scope and Approach:

My approach to projects is characterized by adaptability and meticulous attention to detail. I specialize in leveraging the Python programming language to craft efficient, scalable, and innovative solutions. Having worked on various projects spanning from web development and data analysis to machine learning and automation, I am confident in my ability to deliver results that meet and exceed expectations.

Key Strengths:

1. Python Proficiency: I possess an in-depth understanding of Python and its libraries, enabling me to develop robust and optimized code for a variety of applications.

2. Problem-Solving: My strong problem-solving skills allow me to tackle complex challenges and devise creative solutions that align with project goals.

3. Full-Stack Development: I am skilled in both front-end and back-end development, making me a versatile asset for projects requiring end-to-end solutions.

4. Data Analysis and Visualization: My expertise in data manipulation, analysis, and visualization equips me to extract meaningful insights from datasets of various sizes.

5. Machine Learning and AI: With a background in machine learning, I am adept at implementing algorithms, building models, and deploying AI solutions.

6. API Integration: I have experience integrating various APIs, enabling seamless communication between systems and expanding project capabilities.

7. Project Management: My organized approach and effective communication ensure smooth project execution, timely updates, and collaboration.

Project Scenarios:

Whether you require a web application, data analysis tools, automation scripts, machine learning models, or any other Python-based solution, I am prepared to deliver results that align with your unique project needs. Here are a few examples of projects I can contribute to:

1. Web Development:

   - Design and develop interactive web applications using Django, Flask, or other frameworks.

   - Create responsive user interfaces using HTML, CSS, and JavaScript libraries.

2. Data Analysis and Visualization:

   - Analyze and visualize data using Pandas, Matplotlib, Seaborn, and interactive visualization libraries like Plotly.

3. Machine Learning and AI:

   - Develop and train machine learning models using libraries such as scikit-learn and TensorFlow.

   - Implement natural language processing (NLP) models, computer vision solutions, and predictive analytics.

4. Automation and Scripting:

   - Build automation scripts to streamline repetitive tasks and enhance efficiency.

   - Develop command-line tools and utilities to simplify complex processes.

5. API Integration and Development:

   - Integrate third-party APIs for enhanced functionality, data retrieval, and system interactions.

   - Develop custom APIs to enable data exchange between different components.

Conclusion:

My versatile skill set as a Python developer, combined with my dedication to delivering high-quality solutions, positions me as an ideal partner for a wide range of projects. I am excited about the prospect of collaborating with you to bring your vision to life.

Thank you for considering my proposal. I look forward to the opportunity to contribute to your projects and achieve exceptional results together.

Sincerely,

[Your Name]

[Your Contact Information]

SUMMARY 

In summary, a well-crafted proposal is your golden ticket to new opportunities, connections, and successes. It serves as a powerful tool to showcase your capabilities, solve specific problems, and illustrate why you're the best fit for the job. But remember, writing an effective proposal is not a one-size-fits-all affair. Tailor your language, format, and content to match the unique needs and expectations of your prospective client or partner. With the insights you've gained from this article, you're now well-equipped to write proposals that not only fulfill requirements but also leave a lasting impression. Take that pen, hit those keys, and craft a proposal that opens doors you never knew existed.

I hope these examples help guide your article and inspire your readers to write impactful proposals