shudima/notebooks

Jupyter Notebooks with Deep Learning Tutorials

43
/ 100
Emerging

This project provides practical, step-by-step guides for building deep learning models. It takes you from understanding core concepts like activation functions and text representation to implementing solutions for specific tasks like classifying images, recognizing named entities in text, or performing sentiment analysis. This is ideal for data scientists, machine learning engineers, or researchers looking to learn or apply deep learning techniques through hands-on examples.

209 stars. No commits in the last 6 months.

Use this if you are a data scientist or machine learning engineer who learns best by working through concrete deep learning examples with code.

Not ideal if you are looking for a production-ready library or a comprehensive theoretical deep learning textbook.

deep-learning-tutorials natural-language-processing image-classification neural-networks speech-classification
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 8 / 25
Community 25 / 25

How are scores calculated?

Stars

209

Forks

127

Language

Jupyter Notebook

License

Last pushed

Aug 05, 2019

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/shudima/notebooks"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.