rmi
machine_learning_basics
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| rmi | machine_learning_basics | |
|---|---|---|
| 1 | 5 | |
| 51 | 4,134 | |
| - | - | |
| 0.0 | 0.0 | |
| almost 3 years ago | about 1 year ago | |
| Jupyter Notebook | Jupyter Notebook | |
| Apache License 2.0 | MIT License |
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machine_learning_basics
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Bayesian linear regression in (plain) Python
A while back I open sourced a repository implementing fundamental machine learning algorithms in Python, along with the most important theoretical information. I originally created the repository for myself when preparing for AI residency interviews. You can find the original Reddit post here.
What are some alternatives?
Financial-Models-Numerical-Methods - Collection of notebooks about quantitative finance, with interactive python code.
ML-For-Beginners - 12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
TensorFlow-Examples - TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
100-Days-Of-ML-Code - 100 Days of ML Coding
google-research - Google Research
fastai - The fastai deep learning library
homemade-machine-learning - 🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained
mango - Parallel Hyperparameter Tuning in Python
Made-With-ML - Learn how to design, develop, deploy and iterate on production-grade ML applications.
RadixSpline - A Single-Pass Learned Index
100DaysofMLCode - My journey to learn and grow in the domain of Machine Learning and Artificial Intelligence by performing the #100DaysofMLCode Challenge. Now supported by bright developers adding their learnings :+1: