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README

Machine Learning From Scratch by AssemblyAI

This repository contains the code developed in the Machine Learning from scratch course on YouTube by AssemblyAI. It includes the implementations of popular ML algorithms.

Watch the course on our YouTube channel

The code is based on the similar repository by Python Engineer (Patrick Loeber): https://github.com/python-engineer/MLfromscratch

Core symbols most depended-on inside this repo

plot
called by 8
10 KMeans/kmeans.py
get_hyperplane_value
called by 6
09 SVM/svm.py
_entropy
called by 3
04 Decision Trees/DecisionTree.py
_entropy
called by 3
05 Random Forests/DecisionTree.py
predict
called by 2
02 Linear Regression/LinearRegression.py
euclidean_distance
called by 2
10 KMeans/kmeans.py
sigmoid
called by 2
03 Logistic Regression/LogisticRegression.py
_split
called by 2
04 Decision Trees/DecisionTree.py

Shape

Method 60
Class 13
Function 13

Languages

Python100%

Modules by API surface

05 Random Forests/DecisionTree.py14 symbols
04 Decision Trees/DecisionTree.py14 symbols
10 KMeans/kmeans.py10 symbols
09 SVM/svm.py7 symbols
08 Perceptron/perceptron.py6 symbols
06 NaiveBayes/naive_bayes.py6 symbols
05 Random Forests/RandomForest.py6 symbols
01 KNN/KNN.py6 symbols
03 Logistic Regression/LogisticRegression.py5 symbols
07 PCA/pca.py4 symbols
02 Linear Regression/LinearRegression.py4 symbols
05 Random Forests/train.py1 symbols

For agents

$ claude mcp add Machine-Learning-From-Scratch \
  -- python -m otcore.mcp_server <graph>

⬇ download graph artifact