930 Open source projects that are alternatives of or similar to supervised-machine-learning

An Interactive Approach to Understanding Deep Learning with Keras

This is the implementation of Sparse Projection Oblique Randomer Forest

🍊 📊 💡 Orange: Interactive data analysis

Machine Learning models from scratch with a better visualisation

simple tutorial on Machine Learning with Scikitlearn

Machine learning algorithm such as KNN,Naive Bayes,Logistic Regression,SVM,Decision Trees,Random Forest,k means and Truncated SVD on amazon fine food review

A curated list of data mining papers about fraud detection.

Python code for common Machine Learning Algorithms

🔥🌟《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!

📈 Click-Through Rate Prediction using Logistic Regression and Tree Algorithms

Simple machine learning library / 簡單易用的機器學習套件

Decision Trees, Random Forest, Dynamic Time Warping, Naive Bayes, KNN, Linear Regression, Logistic Regression, Mixture Of Gaussian, Neural Network, PCA, SVD, Gaussian Naive Bayes, Fitting Data to Gaussian, K-Means

Repository for the AdaptiveRandomForest algorithm implemented in MOA 2016-04

🏭 JavaScript Machine Learning Toolkit

Practice and tutorial-style notebooks covering wide variety of machine learning techniques

Text Classification Algorithms: A Survey

Conceptual & empirical comparisons between decision forests & deep networks

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

Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.

Machine Learning University: Decision Trees and Ensemble Methods

A python implementation of C4.5 algorithm by R. Quinlan

A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models.

Material from "Random Forests and Gradient Boosting Machines in R" presented at Machine Learning Day '18

Vídeos e códigos do Universo Discreto ensinando o fundamental de Machine Learning em Python. Para mais detalhes, acompanhar a playlist listada.

A python library for decision tree visualization and model interpretation.

Machine Learning Lectures at the European Space Agency (ESA) in 2018

An example project that predicts risk of credit card default using a Logistic Regression classifier and a 30,000 sample dataset.

文本分类基准测试

Top 5th percentile solution to the Kaggle knowledge problem - Bike Sharing Demand

Machine learning for C# .Net

I will update this repository to learn Machine learning with python with statistics content and materials

Fake News Detection in Python

Collection of stats, modeling, and data science tools in Python and R.

General Assembly's 2015 Data Science course in Washington, DC

A python library to build Model Trees with Linear Models at the leaves.

Machine Learning with the NSL-KDD dataset for Network Intrusion Detection

Workshop (6 hours): preprocessing, cross-validation, lasso, decision trees, random forest, xgboost, superlearner ensembles

several methods for text classification

Final project of IBM's course https://www.coursera.org/learn/machine-learning-with-python on coursera

A Lightweight Decision Tree Framework supporting regular algorithms: ID3, C4,5, CART, CHAID and Regression Trees; some advanced techniques: Gradient Boosting (GBDT, GBRT, GBM), Random Forest and Adaboost w/categorical features support for Python

Projects I completed as a part of Great Learning's PGP - Artificial Intelligence and Machine Learning

Formed trajectories of sets of points.Experimented on finding similarities between trajectories based on DTW (Dynamic Time Warping) and LCSS (Longest Common SubSequence) algorithms.Modeled trajectories as strings based on a Grid representation.Benchmarked KNN, Random Forest, Logistic Regression classification algorithms to classify efficiently t…

Handwritten Digit Recognition using Machine Learning and Deep Learning

Solutions to labs and excercises from An Introduction to Statistical Learning, as Jupyter Notebooks.

Loan Application Data Analysis

In This repository I made some simple to complex methods in machine learning. Here I try to build template style code.

Predicting the winner of 2019 cricket world cup using random forest algorithm

텐서플로우와 머신러닝으로 시작하는 자연어처리(로지스틱회귀부터 트랜스포머 챗봇까지)

Forecast stock prices using machine learning approach. A time series analysis. Employ the Use of Predictive Modeling in Machine Learning to Forecast Stock Return. Approach Used by Hedge Funds to Select Tradeable Stocks

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

MATLAB/Octave library for stochastic optimization algorithms: Version 1.0.20

Misc Statistics and Machine Learning codes in R

Online machine learning methods

This is a Statistical Learning application which will consist of various Machine Learning algorithms and their implementation in R done by me and their in depth interpretation.Documents and reports related to the below mentioned techniques can be found on my Rpubs profile.

Let's you to access your FB account from the command line and returns various things number of unread notifications, messages or friend requests you have.

Predicting Amsterdam house / real estate prices using Ordinary Least Squares-, XGBoost-, KNN-, Lasso-, Ridge-, Polynomial-, Random Forest-, and Neural Network MLP Regression (via scikit-learn)

Heart Disease prediction using 5 algorithms

Go Scoring API for PMML

Ruby Scoring API for PMML

ugtm: a Python package for Generative Topographic Mapping