Fundraising September 15, 2024 – October 1, 2024 About fundraising

Dive into Deep Learning

Main
Computers - Artificial Intelligence (AI)
Dive into Deep Learning

Dive into Deep Learning

Aston Zhang, Zachary C. Lipton, Mu Li, and Alexander J. Smola

5.0 / 0

How much do you like this book?

What’s the quality of the file?

Download the book for quality assessment

What’s the quality of the downloaded files?

Categories:

Computers - Artificial Intelligence (AI)

Year:

2021

Edition:

0.16.1

Publisher:

d2l.ai

Language:

english

Pages:

1021

File:

PDF, 27.61 MB

IPFS:

,

english, 2021

Read Online

Conversion to is in progress

Conversion to is failed

You may be interested in

Kevin P. Murphy — Probabilistic Machine Learning: Advanced Topics - Draft

Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong — Mathematics For Machine Learning

Daniel Jurafsky, James H. Martin — Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition

Kevin P Murphy — Probabilistic Machine Learning: An Introduction Book 1

Hal Daumé III — A Course in Machine Learning

Jason Brownlee — Better Deep Learning: Train Faster, Reduce Overfitting, and Make Better Predictions

Daniel Voigt Godoy — Deep Learning with PyTorch Step-by-Step: A Beginner’s Guide

Daniel Voigt Godoy — Deep Learning with PyTorch Step-by-Step: A Beginner’s Guide

Ian Goodfellow, Yoshua Bengio and Aaron Courville — Deep Learning

Aston Zhang, Zachary C. Lipton, 李沐, and Alexander J. Smola — 动手深度学习-PyTorch(第二版)

Michael Nielsen — Neural Networks and Deep Learning

Dan Jurafsky and James H. Martin — Speech and Language Processing (3rd ed. draft)

Andrew Glassner — Deep Learning, Vol. 2: From Basics to Practice

Andrew Glassner — Deep Learning, Vol. 1: From Basics to Practice

Michael Fullan — Deep Learning: Engage the World Change the World

Andrew Ng — Machine Learning Yearning (Draft Version)

Venelin Valkov — Get Sh*t Done With Pytorch: Solve Real-World Machine Learning Problems

Aston Zhang, Zachary C. Lipton, Mu Li & Alexander J. Smola — Dive into Deep Learning

Andrew Ng — Machine Learning Yearning

Ian Goodfellow, Yoshua Bengio, Aaron Courville — Deep Learning

Sutton, Richard S., Barto, Andrew G. — Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning series)

Kevin P. Murphy — Probabilistic Machine Learning: An Introduction (Adaptive Computation and Machine Learning series)

Simon J.D. Prince — Understanding Deep Learning

Shalom Lappin — Deep Learning and Linguistic Representation

Uday Kamath, Kenneth L. Graham, Wael Emara — Transformers for Machine Learning: A Deep Dive

Christopher M. Bishop — Pattern Recognition and Machine Learning

Stephen Boyd, Lieven Vandenberghe — Convex Optimization

Aston Zhang, Zachary C. Lipton, Mu Li, Alexander J. Smola — Dive into Deep Learning

Chip Huyen — Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications

Dr Simon J. D. Prince — Computer Vision: Models, Learning, and Inference

David L. Poole; Alan K Mackworth — Artificial Intelligence: Foundations of Computational Agents

Vaibhav Verdhan — Computer Vision Using Deep Learning: Neural Network Architectures with Python and Keras

Nikhil Buduma, Nicholas Locascio — Fundamentals of Deep Learning: Designing Next-Generation Machine Intelligence Algorithms

Douwe Osinga — Deep Learning Cookbook: Practical Recipes to Get Started Quickly

Seth Weidman — Deep Learning from Scratch: Building With Python From First Principles

Jeremy Howard; Sylvain Gugger — Deep Learning for Coders with fastai and PyTorch

Jeremy Howard, Sylvain Gugger — Deep Learning for Coders With Fastai and Pytorch: AI Applications Without a PhD

Nikhil Buduma — Fundamentals of Deep Learning: Designing Next-Generation Machine Intelligence Algorithms, 2nd Edition

Joanne Quinn, Joanne McEachen, Michael Fullan, Mag Gardner, Max Drummy — Dive Into Deep Learning : Tools for Engagement

Francois Chollet — Deep Learning with Python, 2nd Edition (Final Release)

Eli Stevens, Luca Antiga, Thomas Viehmann — Deep Learning With Pytorch

Mark Ryan — Deep Learning with Structured Data

Most frequently terms