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    Mastering ChatGPT and Google Colab for Machine Learning: Automate AI Workflows and Fast-Track Your Machine Learning

    Posted By: Free butterfly
    Mastering ChatGPT and Google Colab for Machine Learning: Automate AI Workflows and Fast-Track Your Machine Learning

    Mastering ChatGPT and Google Colab for Machine Learning: Automate AI Workflows and Fast-Track Your Machine Learning Tasks with the Power of ChatGPT, Google Colab, and Python (English Edition) by Rosario Moscato
    English | September 19, 2024 | ISBN: 819795349X | 323 pages | EPUB | 205 Mb

    Learn how to harness the power of ChatGPT to streamline data analysis, accelerate model development, and unlock innovative solutions to real-world problems.

    Book Description
    Unlock the future of machine learning by mastering Google Colab, trusted by over 5 million data scientists, and ChatGPT, powering 100 million users worldwide. This book bridges the latest in AI with practical, hands-on applications for data science.

    With these game-changing tools at your command, you’ll be able to streamline complex workflows, automate tedious tasks, and propel your AI skills to new heights—making machine learning faster, smarter, and more accessible than ever before.

    Each chapter unfolds a specific aspect of data science and machine learning, seamlessly integrated with ChatGPT’s free version capabilities. The foundational chapters introduce key machine learning concepts, while advanced sections explore topics such as natural language processing, sentiment analysis, and predictive analytics—all illustrated with real-world examples and interactive exercises.

    Table of Contents
    1. Introduction to ChatGPT
    2. ChatGPT for Data Science and Machine Learning
    3. Fundamentals of Statistics for Data Science
    4. Missing Values and Outliers
    5. Relation Between Variables and Charts
    6. Data Preparation
    7. Training and Evaluation
    8. Fine Tuning, Features Selection, and Final Model
    9. Data Preparation and Training
    10. Fine Tuning and Final Model
    11. Data Analysis and Dataset Manipulation (NLP)
    12. Sentiment Analysis and Predictions
    13. ChatGPT-4 for a Completely Automated Data Science Workload
    14. Customizing GPT for Applications
    15. Takeaways and Conclusions
    Index

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