Popular GitHub Repositories for Kmeans Smote

AiLearning：数据分析+机器学习实战+线性代数+PyTorch+NLTK+TF2

Code for Tensorflow Machine Learning Cookbook

Plain python implementations of basic machine learning algorithms

Here you can get all the Quantum Machine learning Basics, Algorithms ,Study Materials ,Projects and the descriptions of the projects around the web

A curated list of Best Artificial Intelligence Resources

Synthetic Minority Over-Sampling Technique for Regression

The first machine learning framework that encourages learning ML concepts instead of memorizing class functions.

This repository contains the code which can recognise the alphabets in Indian sign language for blind using opencv and tensorflow.

Toolkit for Apache Spark ML for Feature clean-up, feature Importance calculation suite, Information Gain selection, Distributed SMOTE, Model selection and training, Hyper parameter optimization and selection, Model interprability.

Streaming Anomaly Detection Solution by using Pub/Sub, Dataflow, BQML & Cloud DLP

Play, learn, solve, and analyze No-Limit Texas Hold Em. Implementation follows from Monte Carlo counter-factual regret minimization over with hierarchical K-means imperfect recall abstractions.

This research project will illustrate the use of machine learning and deep learning for predictive analysis in industry 4.0.

Objective of the repository is to learn and build machine learning models using Pytorch. 30DaysofML Using Pytorch

Traditional Machine Learning Models for Large-Scale Datasets in PyTorch.

Handle class imbalance intelligently by using variational auto-encoders to generate synthetic observations of your minority class.

Data Science algorithms and topics that you must know. (Newly Designed) Recommender Systems, Decision Trees, K-Means, LDA, RFM-Segmentation, XGBoost in Python, R, and Scala.

? hCaptcha image label binary model factory (PyTorch Training, Cluster-based Auto Label Tools, Export ONNX model, ONNX model inference)

Using machine learning on your anki collection to enhance the scheduling via semantic clustering and semantic similarity

This clustering based anomaly detection project implements unsupervised clustering algorithms on the NSL-KDD and IDS 2017 datasets

Transforming skincare recommendations: our hybrid system combines KNN, CNN, and EfficientNet B0 for personalized advice. Published in IEEE, with 80% validation accuracy and 87.10% training accuracy.