1223 Open source projects that are alternatives of or similar to MachineLearning

system performance characterization tool based on linux perf

For extensive instructor led learning

Intel(R) Extension for Scikit-learn is a seamless way to speed up your Scikit-learn application

Animated Visualizations of Popular Machine Learning Algorithms

A clustering tutorial with scikit-learn for beginners.

Algorithmic trading using machine learning.

My GitHub blog: things you might be interested, and probably not...

Enhanced BiLSTM Inference Model for Natural Language Inference

Machine Learning for Spot Prices

Vanilla LSTM with numpy

No description or website provided.

Collection of Kaggle Datasets ready to use for Everyone (Looking for contributors)

(Python) transform a document-term matrix to an Okapi/BM25 representation

LSTM sentiment analysis. Please look at my another repo for SVM and Naive algorithem

A gui for tesseractOCR with some preprocessing image options (OpenCV) for improve character recognition

bitcoin prediction algorithms

Classification of Urban Sound Audio Dataset using LSTM-based model.

A library for creating and curating reproducible pipelines for scientific and industrial machine learning

Pyspark in Google Colab: A simple machine learning (Linear Regression) model

This repo contains a PyTorch implementation of a BiLSTM-CRF model for named entity recognition task.

PredRNN: Recurrent Neural Networks for Predictive Learning using Spatiotemporal LSTMs

Video prediction using lstm and unet

RNN-LSTM that learns passwords from a starting list

A collection of ML related stuff including notebooks, codes and a curated list of various useful resources such as books and softwares. Almost everything mentioned here is free (as speech not free food) or open-source.

Predict materials properties using only the composition information!

Feature extraction by using SITF+BoF.

A MATLAB toolbox for classifier: Version 1.0.7

Using LSTM network for time series forecasting

Machine learning in Python with scikit-learn MOOC

A Latent Dirichlet Allocation implementation in Python.

도서 "핸즈온 머신러닝"의 예제와 연습문제를 담은 주피터 노트북입니다.

Techniques & resources for training interpretable ML models, explaining ML models, and debugging ML models.

simple Echo State Networks integrated with scikit-learn

My textbook for teaching Machine Learning

Super fast simple k-means implementation for unidimiensional and multidimensional data.

No description or website provided.

Bidirectional Helmholtz Machines

Markov Chains and Hidden Markov Models in Python

A tool for visualizing the structure and performance of Random Forests 🌳

What and How Well You Performed? A Multitask Learning Approach to Action Quality Assessment [CVPR 2019]

Matlab library for gradient descent algorithms: Version 1.0.1

R package: parallel computing toolset for relatedness and principal component analysis of SNP data (Development Version)

Helm charts for creating reproducible and maintainable deployments of Polyaxon with Kubernetes.

host load prediction with Long Short-Term Memory in cloud computing

Software platform for clinical neuroimaging studies

基於DA-RNN之DSTP-RNN論文試做(Ver1.0)

[ICML 2019, 20 min long talk] Robust Decision Trees Against Adversarial Examples

A library to parse and convert PMML models into Scikit-learn estimators.

An Interactive Approach to Understanding Supervised Learning Algorithms

Comparing FC VAE / FCN VAE / PCA / UMAP on MNIST / FMNIST

crnn.caffe

Gaussian Mixture Convolutional AutoEncoder applied to CT lung scans from the Kaggle Data Science Bowl 2017

A module for allowing the use of multiple metric functions in scikit's cross_val_score

Various cognitive api for machine learning, vision, language intent alalysis. Covers traditional as well as deep learning model design and training.

Recurrent Additive Networks for Tensorflow

Basic Machine Learning implementation with python

Real time face landmarking using decision trees and NN autoencoders

Go Scoring API for PMML

A gentle introduction to machine learning: data handling, linear regression, naive bayes, clustering

Learn the theory, math and code behind different machine learning algorithms and techniques.