Course materials for CSE disciplines
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Updated
May 26, 2024 - Jupyter Notebook
Course materials for CSE disciplines
ML from Scratch using Numpy (Naive Bayes Classifier, KNN, Linear Regression, KMeans, PCA)
Practising Machine Learning. This repository is created for personal use where I can bookmark and keep all my notebooks, notes, bookmarked links, etc. Anyone who is a beginner in ML can refer to it and feel free to fork or open issues.
Classify the chances of having a Heart Attack based on your Heart's Condition.
Explore fundamental machine learning algorithms with the_ml_from_scratch. This project provides hands-on implementations using numpy, ideal for beginners and enthusiasts to build a solid understanding of core concepts.
Machine Learning, learning adventure :)
From scratch implementations of some algorithms in Machine Learning SkLearn style in Python
This is an educational repository designed to demystify the core concepts of machine learning by providing clear and concise implementations of algorithms using pure Python. We've laid the groundwork, allowing you to dive into the details of each algorithm, understand their workings, and apply them to your own projects.
Implementation of Machine Learning Algorithms (KNN, Linear, Logistic, SVM, K-Means, Decision Tree, Naive Bayes) from Scratch using Python & Numpy only
Companion Repo for the book The Applied ML Field Manual, Prithiviraj Damodaran
Library for machine learning where all algorithms are implemented from scratch. Used only numpy.
Tutorial for Harvard Medical School ML from Scratch Series: Transformer from Scratch. Demo the usage of transformer in various domains: Music sheet, audio signal, image generation & discrimination
Scripts of Machine Learning Algorithms from Scratch. Implementations of machine learning models and algorithms using nothing but NumPy with a focus on accessibility. Aims to cover everything from basic to advance.
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