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Deep learning has the reputation as an exclusive domain for math PhDs. Not so. With this book, programmers comfortable with Python will learn how to get started with deep learning right away. Using PyTorch and the fastai deep learning library, you'll learn how to train a model to accomplish a wide range of tasks-including computer vision, natural language processing, tabular data, and generative networks. At the same time, you'll dig progressively into deep learning theory so that by the end of the book you'll have a complete understanding of the math behind the library's functions.

Data mining. --- Natural language processing (Computer science) --- Machine learning. --- Python (Computer program language) --- Artificial intelligence. --- Neural networks (Computer science) --- Data mining --- Machine learning --- Artificial intelligence --- Scripting languages (Computer science) --- NLP (Computer science) --- Electronic data processing --- Human-computer interaction --- Semantic computing --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Learning, Machine --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Exploration de données --- Traitement du langage naturel --- Apprentissage automatique --- deep learning --- data mining --- artificiële intelligentie (AI) --- fastai --- PyTorch