526 Open source projects that are alternatives of or similar to OLSTEC

Daily Dose of Neural Network that Everyone Needs

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Taller SparkR para las Jornadas de Usuarios de R

Extracting Tables from Document Images using a Multi-stage Pipeline for Table Detection and Table Structure Recognition:

Implementing Clustering Algorithms from scratch in MATLAB and Python

A script in python to organize your images by similarity.

A list of popular deep learning models related to classification, segmentation and detection problems

Notes, examples, and Python demos for the textbook "Machine Learning Refined" (published by Cambridge University Press).

python library implementing ensemble methods for regression, classification and visualisation tools including Voronoi tesselations.

The SimNets Architecture's Implementation in Caffe

🧹 Formerly for binary classification with noisy labels. Replaced by cleanlab.

Deeplearning Algorithms Tutorial

The TensorFlow reference implementation of 'GEMSEC: Graph Embedding with Self Clustering' (ASONAM 2019).

Estudo e implementação dos principais algoritmos de Machine Learning em Jupyter Notebooks.

Fast Python Collaborative Filtering for Implicit Feedback Datasets

Java Statistical Analysis Tool, a Java library for Machine Learning

Network Embedding as Matrix Factorization: Unifying DeepWalk, LINE, PTE, and node2vec

Owl's OCaml Interface to Eigen3 C++ Library

CUDA Matrix Factorization Library with Alternating Least Square (ALS)

WTTE-RNN a framework for churn and time to event prediction

A tour through recommendation algorithms in python [IN PROGRESS]

🤖 NanoNeuron is 7 simple JavaScript functions that will give you a feeling of how machines can actually "learn"

A curated list of community detection research papers with implementations.

🎯 A comprehensive gradient-free optimization framework written in Python

PyTorch Implementations For A Series Of Deep Learning-Based Recommendation Models (IN PROGRESS)

Plant Disease Identification Using Convulutional Neural Network

Java-Based Context-aware Recommendation Library

Monthly Series - Top 10 Machine Learning Articles

Exposure Matrix Factorization: modeling user exposure in recommendation

This is a comprehensive ML techniques with python: Define the Problem- Specify Inputs & Outputs- Data Collection- Exploratory data analysis -Data Preprocessing- Model Design- Training- Evaluation

MADS: Model Analysis & Decision Support

This repositary is a combination of different resources lying scattered all over the internet. The reason for making such an repositary is to combine all the valuable resources in a sequential manner, so that it helps every beginners who are in a search of free and structured learning resource for Data Science. For Constant Updates Follow me in …

R package to interface with OpenML

zoofs is a python library for performing feature selection using a variety of nature-inspired wrapper algorithms. The algorithms range from swarm-intelligence to physics-based to Evolutionary. It's easy to use , flexible and powerful tool to reduce your feature size.

An implementation of "Network Representation Learning with Rich Text Information" (IJCAI '15).

Code for Agile Data Science 2.0, O'Reilly 2017, Second Edition

🍊 👎 Add-on for Orange3 to support recommender systems.

A high performance implementation of HDBSCAN clustering.

Python PyTorch (GPU) and NumPy (CPU)-based port of Févotte and Dobigeon's robust-NMF algorithm appearing in "Nonlinear hyperspectral unmixing with robust nonnegative matrix factorization."

MOA is an open source framework for Big Data stream mining. It includes a collection of machine learning algorithms (classification, regression, clustering, outlier detection, concept drift detection and recommender systems) and tools for evaluation.

fastFM: A Library for Factorization Machines

A Python Package for Density Ratio Estimation

Jumping across biomedical contexts using compressive data fusion

🤖 Roadmap to becoming a Machine Learning developer in 2020

An intuitive implementation of spectral clustering on matlab

StellarGraph - Machine Learning on Graphs

A parallel implementation of "graph2vec: Learning Distributed Representations of Graphs" (MLGWorkshop 2017).

Implements common data science methods and machine learning algorithms from scratch in python. Intuition and theory behind the algorithms is also discussed.

Nimfa: Nonnegative matrix factorization in Python

Python Basics, Machine Learning and Deep Learning

Season 2 of @twosigma's artificial intelligence programming challenge

This is a collection of some of the important machine learning algorithms which are implemented with out using any libraries. Libraries such as numpy and pandas are used to improve computational complexity of algorithms

Examples how MLJAR can be used

Continuously Learning Artificial Intelligence Rules Engine (Claire) for Smart Homes

Minimal and clean examples of machine learning algorithms implementations

A comparison between humans, neuroevolution and multilayer perceptrons playing Flapy Bird implemented in Python

All content related to machine learning from my blog

A curated list of Monte Carlo tree search papers with implementations.

"Learning Machine Learning" Course, Bogotá, Colombia 2019 #LML2019