Python Scikit and Python Data Types for Beginners: A Step-By-Step Guide to Data Science Mastery - 2 Books in 1

Table of contents :
**Chapter 1: Introduction to Python Scikit**
**Chapter 2: Setting Up Your Data Science Environment**
**Chapter 3: Exploring Data with Python Scikit**
**Chapter 4: Data Preprocessing and Cleaning**
**Chapter 5: Data Visualization with Python Scikit**
**Chapter 6: Machine Learning Basics**
**Chapter 7: Supervised Learning with Python Scikit**
**Chapter 8: Unsupervised Learning with Python Scikit**
**Chapter 9: Model Evaluation and Selection**
**Chapter 10: Feature Engineering and Selection**
**Chapter 11: Deep Learning with Python Scikit**
**Chapter 12: Natural Language Processing**
**Chapter 13: Time Series Analysis**
**Chapter 14: Advanced Topics in Data Science**
**Chapter 15: Conclusion and Next Steps**
# Chapter 1: Introduction to Python Data Types
# Chapter 2: The Fundamentals: Understanding Numeric Data Types
# Chapter 3: Strings and Beyond: Exploring Textual Data Types
# Chapter 4: Lists and Tuples: Navigating Ordered Data Structures
# Chapter 5: Dictionaries: Unraveling Key-Value Pairs
# Chapter 6: Sets: Mastering Unordered Collections
# Chapter 7: Booleans: Decoding True and False in Python
# Chapter 8: Variables and Assignments: A Foundation for Data Handling
# Chapter 9: Type Conversion: Bridging the Gap Between Data Types
# Chapter 10: Operations on Data Types: Arithmetic, Concatenation, and More
# Chapter 11: Conditional Statements: Making Decisions with Python
# Chapter 12: Loops: Iterating Through Data Like a Pro
# Chapter 13: Functions: Organizing Code for Reusability
# Chapter 14: Error Handling: Navigating Python's Exceptional Side
# Chapter 15: Advanced Concepts: Generators, Decorators, and More