leriomaggio/deep-learning-keras-tensorflow resource

Health v2 · maintenance only

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2968 stars · 1249 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A Jupyter Notebook tutorial series introducing deep neural networks using Keras and TensorFlow, covering perceptrons, CNNs, autoencoders, and RNNs. It is structured as a hands-on course with examples on datasets like MNIST and word embeddings.

Use cases

• learn deep learning with keras and tensorflow
• jupyter notebook tutorial on neural networks
• understand convolutional neural networks with mnist examples
• learn lstm and recurrent neural networks
• introduction to autoencoders and embeddings
• transfer learning and fine-tuning tutorial
• learn theano tensorflow and keras basics

When to choose

• you want a structured, notebook-based introduction to deep learning fundamentals
• you prefer learning Keras through hands-on MNIST and word2vec examples
• you need coverage of CNNs, RNNs, and autoencoders in one course

When to avoid

• you need up-to-date APIs for the latest TensorFlow or Keras versions
• you want production deep-learning code rather than educational material
• you need advanced topics like transformers or large language models

Facets

learning-resource · maturity maintenance

deep-learning machine-learning nlp computer-vision deep-learning machine-learning tutorials computer-vision python cross-platform keras tensorflow jupyter-notebooks tutorial neural-networks cnn rnn lstm autoencoders transfer-learning natural-language-processing

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