adeshpande3/Tensorflow-Programs-and-Tutorials resource

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1055 stars · 316 forks observed · 2026-08-28

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

A collection of Jupyter Notebook tutorials implementing popular deep learning concepts like CNNs, RNNs, and GANs in TensorFlow. It also includes experiments reproducing ideas from recent research papers.

Use cases

• learn how to implement a CNN in TensorFlow
• understand how GANs work with code examples
• train a character-level RNN for text generation
• study how noisy labels affect CNN training
• get started with TensorFlow deep learning tutorials
• see linear and logistic regression implemented in TensorFlow

When to choose

• you are learning deep learning fundamentals through hands-on notebooks
• you want readable TensorFlow 1.x-style implementations of classic models
• you want paper-inspired experiments explained step by step

When to avoid

• you need production-ready or maintained TensorFlow 2.x code
• you need a library or framework to depend on rather than educational notebooks
• you need up-to-date best practices, as the repo has not been updated since 2018

Facets

learning-resource · maturity abandoned

deep-learning machine-learning deep-learning machine-learning tutorials python tensorflow jupyter-notebooks cnn rnn gan educational

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