KEY FEATURES
● Step-by-step progression from foundational machine learning concepts to advanced techniques using ChatGPT and Google Colab.
● Clear and detailed instructions for data preparation, model training, and evaluation, simplifying complex machine learning tasks.
● Extensive use of Google Colab for coding and experimentation, providing a real-world platform to apply learned techniques effectively.
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. The later chapters focus on optimizing tasks using the more powerful paid version of ChatGPT, culminating in the creation of a custom GPT named “Data Scientist” to tackle specialized challenges.
Additionally, the book includes a section on best practices, expert tips, and interview questions, making it a comprehensive resource for aspiring data scientists and seasoned professionals alike.
WHAT WILL YOU LEARN
● Learn to integrate and optimize ChatGPT and Google Colab for enhanced data science tasks.
● Master techniques for preparing and cleaning data for analysis.
● Gain a solid grasp of statistical concepts essential for data science.
● Learn the processes for training, evaluating, and refining machine learning models.
● Perform data analysis and preprocessing using natural language processing techniques.
● Customize and deploy GPT models for specific data science applications.
WHO IS THIS BOOK FOR?
This book is ideal for aspiring data scientists and machine learning enthusiasts eager to enhance their skills with ChatGPT and Google Colab. It also serves tech professionals, academics, and business analysts seeking practical insights into AI and data science. A basic understanding of programming, statistics, and data analysis is recommended before diving in.
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
Rosario Moscato holds a master’s degree in electronic engineering from Federico II University in Naples and a master’s degree in internet software design from CEFRIEL in Milan. Additionally, he has a diploma in apologetics and a master’s degree in science and faith from the Pontifical Athenaeum Regina Apostolorum in Rome. With nearly 25 years of experience, Rosario has always focused on the development and fine-tuning of the most innovative technologies across various international companies in Europe and Asia, covering various highly technical, commercial, and business development roles.
In recent years, Rosario has turned his focus exclusively towards artificial intelligence and data science. On one hand, he aims to enhance and make every business extremely competitive by introducing and supporting machine and deep learning technologies; and on the other hand, he analyzes the ethical and philosophical implications deriving from the new scenarios that these disciplines open up. Rosario has authored three books and is a speaker at international research centers and conferences, as well as a trainer and technical/scientific consultant in the huge and ever-evolving field of AI.
He is also an author of a weekly magazine and a TV guest. Currently, he is working as the CTO (Chief Technical Officer) and CAIO (Chief Artificial Intelligence Officer) with one of the oldest AI companies in Italy.