Python & Python Library with Artificial Intelligence by Aravind choudhary

Python & Python Library with Artificial Intelligence is a practical and comprehensive guide to learning Artificial Intelligence using Python and its powerful ecosystem of libraries. The book starts with Python programming fundamentals and gradually progresses through data processing, Machine Learning, Deep Learning, Natural Language Processing, and Generative AI. Readers will learn how to use popular Python libraries such as NumPy, Pandas, Matplotlib, Seaborn, Scikit-Learn, TensorFlow, PyTorch, NLTK, spaCy, and Hugging Face to process data, develop intelligent models, analyze text, and build modern AI applications. The book combines concepts with practical Python examples, exercises, and real-world projects, making it useful for beginners, students, Python developers, and aspiring Artificial Intelligence professionals. What You Will Learn Python programming fundamentals 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 and package management NumPy for numerical computing Arrays, indexing, slicing, and broadcasting Pandas for data analysis Series and DataFrames Data cleaning and preprocessing CSV, Excel, JSON, and dataset handling Matplotlib and Seaborn for data visualization Introduction to Artificial Intelligence AI concepts, applications, and workflows Machine Learning fundamentals Supervised and Unsupervised Learning Feature engineering and feature selection Scikit-Learn for Machine Learning Linear Regression Logistic Regression K-Nearest Neighbors Decision Trees and Random Forest Support Vector Machines Naive Bayes K-Means Clustering Principal Component Analysis Model evaluation and performance metrics Cross-validation and hyperparameter tuning Overfitting and underfitting Introduction to Deep Learning Artificial Neural Networks TensorFlow and Keras PyTorch fundamentals Activation functions and optimization CNN, RNN, and LSTM Natural Language Processing with Python NLTK and spaCy Text preprocessing and classification Sentiment analysis Introduction to Transformers Hugging Face libraries and models 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 AI APIs and Python libraries Model saving, loading, and deployment Building intelligent applications with Python Practical Artificial Intelligence projects