Implementing machine learning algorithms from scratch.
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Updated
Sep 11, 2021 - Python
Implementing machine learning algorithms from scratch.
The first machine learning framework that encourages learning ML concepts instead of memorizing class functions.
This repository explores the variety of techniques and algorithms commonly used in machine learning and the implementation in MATLAB and PYTHON.
Learn to build a basic machine learning model from scratch with this repo and tutorial series.
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eXtreme MultiLabel Classification tutorial notebook for Machine Learners (with video)
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Machine Learning Algorithms implemented in Python
Dry Natural Gas Production Prediction of the United States
Cross-platform GUI tool to create and manage (machine learning) configurations and run them automatically and remotely.
All my learnings from "Machine Learning with Python" course offered by "IBM" on Coursera are reflected here.
A machine learning library created in python by Okerew
Going through the book "Python Machine Learning" by Sabastian Raschka and Vahid Mirjalili
Python code (including ipython notebook) for naive bayes classifier to classify salaries of adults based on various attributes
An intermediate level course of machine learning offered by IBM on Cognitive Class.io
This module extends the kernel SHAP method (as introduced by Lundberg and Lee (2017)) which is local in nature, to a method that computes global SHAP values.
Eroji is a simple Python script that uses the DeepFace library to detect faces in an image and recognize the emotions, gender and race of the detected faces.
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