xiaohu2015/DeepLearning_tutorials resource

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

1841 stars · 759 forks observed · 2026-08-28

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

A collection of deep learning algorithms (MLP, CNN, autoencoders, RBM, DBN, and modern CNN architectures) implemented from scratch in TensorFlow for educational purposes, modeled after the classic Theano Deep Learning Tutorials. It is a tutorial codebase of Jupyter notebooks and Python scripts rather than a production library.

Use cases

• learn how classic deep learning models are implemented in tensorflow
• study implementations of rbm and deep belief networks
• understand cnn architectures like mobilenet and densenet from scratch
• tutorial code for logistic regression and mlp in tensorflow
• reference implementations of yolov1 object detection

When to choose

• you want readable, from-scratch implementations of classic deep learning models for study
• you are learning fundamentals of tensorflow 1.x and neural network basics

When to avoid

• you need a maintained library for production deep learning
• you use modern tensorflow 2.x or pytorch versions
• you need supported, tested model implementations

Facets

learning-resource · maturity abandoned

deep-learning machine-learning deep-learning machine-learning tutorials python tensorflow jupyter-notebook educational cnn autoencoder rbm object-detection

Member repositories

For agents

markdown · JSON · MCP: product_card(name="xiaohu2015/DeepLearning_tutorials")