Python with Artificial Intelligence by Aravind choudhary

Python with Artificial Intelligence is a practical and comprehensive guide to learning Artificial Intelligence using Python. The book takes readers from Python programming fundamentals to Machine Learning, Deep Learning, Natural Language Processing, and Generative AI. Readers will learn how to use popular Python libraries and frameworks to process data, build intelligent systems, train Machine Learning models, work with neural networks, and develop practical AI applications. The book follows a step-by-step approach, combining theoretical concepts with practical Python examples and real-world projects. It is designed to help beginners and developers build a strong foundation in Artificial Intelligence and understand how modern AI applications are developed using Python. What You Will Learn Python programming fundamentals for Artificial Intelligence Variables, data types, operators, and control statements Functions, modules, packages, and exception handling Lists, tuples, sets, and dictionaries Object-Oriented Programming with Python File handling and JSON processing Python libraries for AI and Data Science NumPy for numerical computing Pandas for data analysis Matplotlib and Seaborn for data visualization Introduction to Artificial Intelligence AI concepts, applications, and real-world use cases Types of Artificial Intelligence Machine Learning fundamentals Supervised and Unsupervised Learning Data preprocessing and feature engineering Linear and Logistic Regression K-Nearest Neighbors Decision Trees and Random Forest Support Vector Machines Naive Bayes K-Means Clustering Principal Component Analysis Machine Learning model evaluation Scikit-Learn for AI development Introduction to Deep Learning Neural Networks and Artificial Neural Networks Activation functions and optimization Forward propagation and backpropagation Introduction to CNN, RNN, and LSTM Natural Language Processing with Python Text preprocessing and tokenization Text classification and sentiment analysis Introduction to Transformers Introduction to Large Language Models (LLMs) Generative AI fundamentals Prompt Engineering AI-powered text generation Embeddings and semantic search Retrieval-Augmented Generation (RAG) Introduction to AI Agents Tool calling and AI automation Working with modern AI APIs and Python libraries Building intelligent applications with Python AI model evaluation and deployment Real-world Artificial Intelligence projects