bsc-iitm/ML_Handbook
Empower ML students with hands-on experience. Explore diverse datasets, demystify 'black box' models, and bridge theory with practice. Delve into machine learning with Colab notebooks and in-depth reports. Open source for accessible learning.
This handbook helps aspiring machine learning practitioners understand complex models and workflows by providing practical, interactive examples. It takes real-world datasets and guides you through data preparation, exploration, model building, and interpretation, enabling you to build and explain machine learning solutions. This resource is for students, self-learners, or anyone looking to develop their practical machine learning skills.
No commits in the last 6 months.
Use this if you want hands-on experience applying machine learning theory to diverse datasets and understanding how models work beyond just their output.
Not ideal if you are an experienced machine learning engineer looking for advanced research, novel algorithms, or production-ready deployment tools.
Stars
9
Forks
4
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Jun 10, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/bsc-iitm/ML_Handbook"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
numerai/example-scripts
A collection of scripts and notebooks to help you get started quickly.
musicinformationretrieval/musicinformationretrieval.com
Instructional notebooks on music information retrieval.
Arm-Examples/ML-examples
Arm Machine Learning tutorials and examples
trekhleb/homemade-machine-learning
🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math...
akabe/ocaml-jupyter
An OCaml kernel for Jupyter (IPython) notebook