"Written by three experts in the field, Deep Learning is the only comprehensive book on the subject."
--Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX
Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.
The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.
Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.
Yoshua Bengio is Professor of Computer Science at the Université de Montréal.
Aaron Courville is Assistant Professor of Computer Science at the Université de Montréal.
#PhD in #Economics and #MachineLearning, passionate about #AI, #technology, #politics, #finance, #philosophy, #workout and #chess. From 🇮🇹 living in 🇱🇺
Here it is a Venn diagram properly explaining the relationship among #AI, #MachineLearning, and #deeplearning . It comes from a cornerstone book in the discipline: “Deep Learning” by Ian Goodfellow, Yoshua Bengio and Aaron Courveille, so you can safely take it for granted. https://t.co/zutnA8tauY
Self-taught Machine Learning Enthusiast 🤖 | Aspiring AI Engineer 🚀 | Passionate about unlocking the potential of AI | Embracing the power of Rust 🦀|
Doing some deep deep learning. Thanks to @geoffreyhinton @goodfellow_ian #BooksWorthReading #ArtificialIntelligence #MachineLearning https://t.co/yLaKTszZBq
🎓 M. Sc. Data Science | We write about AI, Software Engineering and Investment Research. | Founder @towardsfinance | Tesla Investor | https://t.co/BhIa3czizu
📚 These must-read books bring your #DataScience Skills to the next level! 1️⃣ "The Elements of Statistical Learning" by Trevor Hastie and others 2️⃣ "Python Crash Course" by Eric Matthes 3️⃣ "Deep Learning" by Ian Goodfellow and others Expand your horizons, and happy reading! 📖