dair-ai/ML-Notebooks
:fire: Machine Learning Notebooks
This resource provides a collection of interactive code examples for learning and experimenting with machine learning. You can input various datasets, like text or image data, to train and test different models. The output is a working machine learning model that can be used for tasks like classifying images or text. This is ideal for students, researchers, or anyone new to machine learning who wants hands-on experience.
3,436 stars. No commits in the last 6 months.
Use this if you are learning machine learning concepts and need practical, runnable examples to understand how algorithms and models work.
Not ideal if you are looking for production-ready solutions or a comprehensive library for advanced machine learning applications without significant modification.
Stars
3,436
Forks
535
Language
Jupyter Notebook
License
Apache-2.0
Category
Last pushed
Apr 09, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/dair-ai/ML-Notebooks"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
dcavar/python-tutorial-notebooks
Python tutorials as Jupyter Notebooks for NLP, ML, AI
aws-neuron/aws-neuron-samples
Example code for AWS Neuron SDK developers building inference and training applications
amrzv/awesome-colab-notebooks
Collection of google colaboratory notebooks for fast and easy experiments
trekhleb/machine-learning-experiments
🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo
deepklarity/jupyter-text2code
A proof-of-concept jupyter extension which converts english queries into relevant python code