Python Library with Artificial Intelligence by Aravind choudhary

Python Library with Artificial Intelligence is a practical and comprehensive guide to using powerful Python libraries for developing Artificial Intelligence applications. The book begins with Python programming and essential libraries and gradually progresses toward 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, build intelligent models, analyze text, and develop modern AI applications. The book combines fundamental concepts with practical Python examples and real-world projects, making it suitable for students, beginners, Python developers, and aspiring AI professionals. What You Will Learn Python programming fundamentals for AI Python modules, packages, and libraries 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 Data preprocessing and feature engineering Scikit-Learn for Machine Learning Linear and 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 Neural Networks and Artificial Neural Networks TensorFlow and Keras PyTorch fundamentals Activation functions and optimization CNN, RNN, and LSTM fundamentals Natural Language Processing with Python NLTK and spaCy Text preprocessing and text 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 real-world AI applications Practical Artificial Intelligence projects