curiousily/Machine-Learning-from-Scratch
Succinct Machine Learning algorithm implementations from scratch in Python, solving real-world problems (Notebooks and Book). Examples of Logistic Regression, Linear Regression, Decision Trees, K-means clustering, Sentiment Analysis, Recommender Systems, Neural Networks and Reinforcement Learning.
This project helps aspiring machine learning practitioners understand how core algorithms work by showing their complete implementation in Python. It takes raw data and demonstrates how to build models for tasks like predicting outcomes, grouping similar items, or recommending products. This is ideal for students, data scientists, or engineers who want to grasp the inner workings of machine learning.
189 stars. No commits in the last 6 months.
Use this if you want to learn the fundamental mechanics of machine learning algorithms by seeing them built step-by-step.
Not ideal if you're looking for a tool to apply machine learning models immediately without diving into their underlying code.
Stars
189
Forks
67
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Jul 05, 2023
Commits (30d)
0
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