Скачать или смотреть Classification Neural Network Visualizer

This is an interactive visualization of a neural network designed for binary classification. The model learns to separate two classes through training, with each plot below illustrating a different aspect of the learning process and network behavior.

How to use this tool: Use the sliders or play/pause buttons below each plot to animate the training process epoch by epoch. This lets you observe how the neural network structure, activations, loss, and gradients evolve as learning progresses.

See it in action:
https://nn-visualizer.com

Hover over nodes, connections, or curves to see more detailed information. For a focused study, use the epoch slider to stop and analyze any moment in the training timeline.

About the Creator
Dido Grigorov
https://www.linkedin.com/in/didogrigorov/

Dido is a seasoned Deep Learning Engineer and Python programmer with an impressive 17 years of experience in the field. He is currently pursuing advanced studies at the prestigious Stanford University, where he is enrolled in a cutting-edge AI program led by renowned experts such as Andrew Ng, Christopher Manning, Fei-Fei Li, and Chelsea Finn, providing Dido with unparalleled insights and mentorship.

Dido’s passion for Artificial Intelligence is evident in his dedication to both work and experimentation. Over the years, he has developed a deep expertise in designing, implementing, and optimizing machine learning models. His proficiency in Python has enabled him to tackle complex problems and contribute to innovative AI solutions across various domains.

Author for Springer Nature

Dido is the author of two books for the prestigious Springer Nature, adopted and approved by more than 300 academic libraries, including MIT, Harvard, Stanford, Carnegie Mellon, Northeastern University, the New York University School of Medicine, Colorado State University, and the Sunnyvale Public Library:

1. Introduction to Python and Large Language Models (approved by 300+ academic libraries)

https://link.springer.com/book/10.1007/979...

2. Intermediate Python and Large Language Models