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 blog.ephorie.de
Logistic Regression as the Smallest Possible Neural Network - Learning Machines
| | blog.vstelt.dev
Writing a Neural Network from Scratch in Rust
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| | [AI summary] The article explains the process of building a neural network from scratch in Rust, covering forward and backward propagation, matrix operations, and code implementation.
| | golb.hplar.ch
Building a simple neural network with Java and JavaScript
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| | [AI summary] The blog post details the author's experience implementing a feedforward neural network for digit recognition using Java and JavaScript, explaining the underlying algorithms, shared external libraries, and architectural decisions while reviewing an introductory book on the topic.
| | dennybritz.com
Implementing a Neural Network from Scratch in Python ยท Denny's Blog
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| | All the code is also available as an Jupyter notebook on Github.
| | blog.keras.io
Building Autoencoders in Keras
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| [AI summary] The text discusses various types of autoencoders and their applications. It starts with basic autoencoders, then moves to sparse autoencoders, deep autoencoders, and sequence-to-sequence autoencoders. The text also covers variational autoencoders (VAEs), explaining their structure and training process. It includes code examples for each type of autoencoder and mentions the use of tools like TensorBoard for visualization. The VAE section highlights how to generate new data samples and visualize the latent space. The text concludes with references and a note about the potential for further topics.