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10 Weeks, 20 Lessons, Data Science for All!
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 instead.
PRML algorithms implemented in Python
Free MLOps course from DataTalks.Club
Tutorials, assignments, and competitions for MIT Deep Learning related courses.
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
Notebooks for learning deep learning
Tutorials on getting started with PyTorch and TorchText for sentiment analysis.
My solution to the book A Collection of Data Science Take-Home Challenges
The Hitchhiker's Guide to Data Science for Social Good
Hands-On Reinforcement Learning with Python, published by Packt
Machine learning course materials.
These are my notes which I prepared during deep learning specialization taught by AI guru Andrew NG. I have used diagrams and code snippets from the code whenever needed but following The Honor Code.
Achieve your marketing goals with the data analytics power of Python
A Portfolio of my Data Science Projects
The compiled, clean (not run) Jupyter notebooks for Elegant SciPy
Class resources for CAPP 30254 (Machine Learning for Public Policy)
ECON 815: Computational Methods for Economists
Jupyter notebooks for Computational Content Analysis
Jupyter Notebooks to follow for each week
This is the course repository for the Spring 2020 iteration of MACS 30123 "Large-Scale Computing for the Social Sciences" at the University of Chicago.
Main Course Repository for Computational Methods in Economics (Econ 21410, Spring 2018)
Contains sample python codes for general topics.
cxic-mit / MLforPublicPolicy
Forked from dssg/MLforPublicPolicyClass resources for CAPP 30254 (Machine Learning for Public Policy)
Tutorials, assignments, and competitions for MIT Deep Learning related courses.