Python Learning Hub
The complete Python learning resource — from fundamentals to deep learning, with detailed explanations, code examples, return values, and step-by-step breakdowns extracted from leading textbooks.
📖 Learning Chapters
Python Fundamentals
Variables, data types, control flow, loops, functions, strings, lists, dicts, file I/O
Object-Oriented Programming
Classes, objects, inheritance, polymorphism, encapsulation, magic methods
Advanced Python
Generators, comprehensions, lambda, context managers, async/await
NumPy
Arrays, operations, indexing, reshaping, math functions, linear algebra
Pandas
Series, DataFrames, data cleaning, groupby, merging, visualization
Machine Learning
Linear/logistic regression, decision trees, SVM, KNN, clustering, evaluation
Deep Learning
Neural networks, backpropagation, CNN, RNN/LSTM, Transformers
Data Analysis
EDA, preprocessing, feature engineering, Matplotlib, Seaborn
Practical Resources
140+ Basic Programs, Interview Questions, and Cheat Sheets
📚 Reference Textbooks
Python Programming
Core language reference with practical examples
FundamentalsPython for Data Analysis
Pandas, NumPy and IPython — by Wes McKinney
Data ScienceNumPy User Guide
Official NumPy documentation and user manual
NumPyMachine Learning with Python Cookbook
Practical solutions from preprocessing to deep learning
Machine LearningLearning scikit-learn
Machine learning in Python with scikit-learn
Scikit-learnDeep Learning — Ian Goodfellow
The definitive textbook on deep learning theory
Deep LearningData Science & Analytics with Python
Comprehensive data science workflow guide
Data ScienceML Engineering eBook
End-to-end machine learning engineering practices
MLOps