Made-With-ML VS stanford-cs229

Compare Made-With-ML vs stanford-cs229 and see what are their differences.

stanford-cs229

πŸ€– Exercise answers to the problem sets from the 2017 machine learning course cs229 by Andrew Ng at Stanford (by zyxue)
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Made-With-ML stanford-cs229
51 8
35,291 0
- -
6.8 0.8
4 months ago over 2 years ago
Jupyter Notebook Jupyter Notebook
MIT License -
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Made-With-ML

Posts with mentions or reviews of Made-With-ML. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-06-25.

stanford-cs229

Posts with mentions or reviews of stanford-cs229. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning stanford-cs229 yet.
Tracking mentions began in Dec 2020.

What are some alternatives?

When comparing Made-With-ML and stanford-cs229 you can also consider the following projects:

cs229-solution - CS229 Solution (summer 2019, 2020).

cs231n - Note and Assignments for CS231n: Convolutional Neural Networks for Visual Recognition

zero-to-mastery-ml - All course materials for the Zero to Mastery Machine Learning and Data Science course.

FLAML - A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.

practical-mlops-book - [Book-2021] Practical MLOps O'Reilly Book

mlops-zoomcamp - Free MLOps course from DataTalks.Club

mlops-course - Learn how to design, develop, deploy and iterate on production-grade ML applications.

cs229-2018-autumn - All notes and materials for the CS229: Machine Learning course by Stanford University

Copulas - A library to model multivariate data using copulas.

coursera-deep-learning-specialization - Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models

ETCI-2021-Competition-on-Flood-Detection - Experiments on Flood Segmentation on Sentinel-1 SAR Imagery with Cyclical Pseudo Labeling and Noisy Student Training

awesome-mlops - A curated list of references for MLOps