
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)
- English
- ePUB (mobile friendly)
- Available on iOS & Android
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)
About this book
Learn how to harness the power of ChatGPT to streamline data analysis, accelerate model development, and unlock innovative solutions to real-world problems.
Book DescriptionUnlock 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 Contents1. Introduction to ChatGPT2. ChatGPT for Data Science and Machine Learning3. Fundamentals of Statistics for Data Science4. Missing Values and Outliers5. Relation Between Variables and Charts6. Data Preparation7. Training and Evaluation8. Fine Tuning, Features Selection, and Final Model9. Data Preparation and Training10. Fine Tuning and Final Model11. Data Analysis and Dataset Manipulation (NLP)12. Sentiment Analysis and Predictions13. ChatGPT-4 for a Completely Automated Data Science Workload14. Customizing GPT for Applications15. Takeaways and Conclusions Index
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Information
Table of contents
- Cover Page
- Title Page
- Copyright Page
- Dedication Page
- About the Author
- About the Technical Reviewers
- Acknowledgements
- Preface
- Get a Free eBook
- Errata
- 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