leriomaggio/deep-learning-keras-tensorflowGitHub
Keras/TensorFlow teaching notebooks; choose for modern-framework DL introduction.
Introduction to Deep Neural Networks with Keras and Tensorflow
- 3.0k
- Jupyter Notebook
- MIT
dormant3.2y ago
mnielsen/neural-networks-and-deep-learning Alternatives
deep learning education / neural network code samples
Python 2 code samples for Michael Nielsen's book 'Neural Networks and Deep Learning', implementing feedforward networks and backpropagation with Theano.
Same job, different approach
Solves the same problem with a different architecture or at a different layer. Expect to rewrite the integration.
fchollet/deep-learning-with-python-notebooksGitHub
Companion code for Keras book; choose to follow that book's examples.
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
- 20.3k
- Jupyter Notebook
- MIT
slowing1.1y ago
dragen1860/Deep-Learning-with-TensorFlow-bookGitHub
Companion code for a TensorFlow 2 DL book; use for modern TF examples.
深度学习入门开源书，基于TensorFlow 2.0案例实战。Open source Deep Learning book, based on TensorFlow 2.0 framework.
- 13.2k
- Jupyter Notebook
- none
dormant5.1y ago
microsoft/samples-for-aiGitHub
Curated deep-learning samples across frameworks; use for concise examples without a book.
Samples for getting started with deep learning across TensorFlow, CNTK, Theano and more.
- 600
- C#
- MIT
dormant3.3y ago
Older generation, or narrower
An earlier or more limited way to do the job. Still the right call when you need something small, proven, or CPU-only.
Newmu/Theano-TutorialsGitHub
Older Theano ML tutorials, narrower than the seed book code.
Bare bones introduction to machine learning from linear regression to convolutional neural networks using Theano.
- 1.3k
- Python
- MIT
dormant10.9y ago
Listed as an alternative to
These projects were analysed and named neural-networks-and-deep-learning among their alternatives. The relationship is not symmetric — how neural-networks-and-deep-learning rates them is a separate judgement, made when neural-networks-and-deep-learning is analysed in its own right.
ageron/handson-mlGitHub
calls neural-networks-and-deep-learning “Choose for the classic NN/DL book that explains backprop from scratch, but only covers neural networks and is dated.”
⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 or handson-mlp instead.
25.6kJupyter Notebookactive
fchollet/deep-learning-with-python-notebooksGitHub
calls neural-networks-and-deep-learning “choose it for Nielsen's classic deep learning book code, though it is unmaintained.”
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
20.3kJupyter Notebookslowing
janishar/mit-deep-learning-book-pdfGitHub
calls neural-networks-and-deep-learning “Older code-oriented intro to neural networks; choose it for a shorter, classical treatment than the MIT book.”
MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville
14.2kJavaslowing