A curated list of Best Artificial Intelligence Resources

gesture recognition toolkit

M. Beyeler (2017). Machine Learning for OpenCV: Intelligent image processing with Python. Packt Publishing Ltd., ISBN 978-178398028-4.

Building and training Speech Emotion Recognizer that predicts human emotions using Python, Sci-kit learn and Keras

Code for training and test machine learning classifiers on MIT-BIH Arrhyhtmia database

🔥🌟《Machine Learning 格物志》: ML + DL + RL basic codes and notes by sklearn, PyTorch, TensorFlow, Keras & the most important, from scratch!💪 This repository is ALL You Need!

An Architecture Combining Convolutional Neural Network (CNN) and Linear Support Vector Machine (SVM) for Image Classification

Learning to create Machine Learning Algorithms

MNIST digit classification with scikit-learn and Support Vector Machine (SVM) algorithm.

Python machine learning applications in image processing, recommender system, matrix completion, netflix problem and algorithm implementations including Co-clustering, Funk SVD, SVD++, Non-negative Matrix Factorization, Koren Neighborhood Model, Koren Integrated Model, Dawid-Skene, Platt-Burges, Expectation Maximization, Factor Analysis, ISTA, FISTA, ADMM, Gaussian Mixture Model, OPTICS, DBSCAN, Random Forest, Decision Tree, Support Vector Machine, Independent Component Analysis, Latent Semantic Indexing, Principal Component Analysis, Singular Value Decomposition, K Nearest Neighbors, K Means, Naïve Bayes Mixture Model, Gaussian Discriminant Analysis, Newton Method, Coordinate Descent, Gradient Descent, Elastic Net Regression, Ridge Regression, Lasso Regression, Least Squares, Logistic Regression, Linear Regression

目标是提供一个完整的Java机器学习(Machine Learning/ML)框架,作为人工智能在学术界与工业界的桥梁. 让相关领域的研发人员能够在各种软硬件环境/数据结构/算法/模型之间无缝切换. 涵盖了从数据处理到模型的训练与评估各个环节,支持硬件加速和并行计算,是最快最全的Java机器学习库.

30 Semi-Supervised Learning Algorithms

[ICMLC 2018] A Neural Network Architecture Combining Gated Recurrent Unit (GRU) and Support Vector Machine (SVM) for Intrusion Detection

Towards Building an Intelligent Anti-Malware System: A Deep Learning Approach using Support Vector Machine for Malware Classification

:v: :ok_hand: :fist: :camera: Sign Language Recognition using Python

Ordinal Regression and Classification Algorithms

Machine learning semantic segmentation - Random Forest, SVM, GBC

Vehicle detection, tracking and counting by SVM is trained with HOG features using OpenCV on c++.

LIBSVM for the browser and nodejs :fire:

Machine learning and scientific computing (linear algebra, statistics, optimization) javascript libraries, with an online lab.

[ICMLSC 2018] On Breast Cancer Detection: An Application of Machine Learning Algorithms on the Wisconsin Diagnostic Dataset

Using Tensorflow and a Support Vector Machine to Create an Image Classifications Engine

Image Classification with `sklearn.svm`

A conceptual model to detect and verify signatures on bank cheques. This is our Final Year project at Thapar Institute of Engineering and Technology.

Apply modern, deep learning techniques for anomaly detection to identify network intrusions.

An Interactive Approach to Understanding Deep Learning with Keras

R package to tune parameters for machine learning(Support Vector Machine, Random Forest, and Xgboost), using bayesian optimization with gaussian process

A demonstration of how to use PyTorch to implement Support Vector Machine with L2 regularizition and multiclass hinge loss

AI Powered Smart Farming Assistant uses advanced technology, including machine learning and CNNs, to provide farmers with crop recommendations, disease identification, weather forecasts, fertilizer recommendation, and crop management guidance through a user-friendly web app.

Forecasting weather Using Multinomial Logistic Regression, Decision Tree, Naïve Bayes Multinomial, and Support Vector Machine