Python package for Bayesian Machine Learning with scikit-learn API Installing & Upgrading package pip install https://github.com/AmazaspShumik/sklearn

PyConverse Let me try first Installation pip install pyconverse Usage Please try this notebook that demos the core functionalities: basic usage noteb

AutoViz Automatically Visualize any dataset, any size with a single line of code. AutoViz performs automatic visualization of any dataset with one lin

Auto-ViML Automatically Build Variant Interpretable ML models fast! Auto_ViML is pronounced "auto vimal" (autovimal logo created by Sanket Ghanmare) N

m2cgen (Model 2 Code Generator) - is a lightweight library which provides an easy way to transpile trained statistical models into a native code

auto_ml Automated machine learning for production and analytics Installation pip install auto_ml Getting started from auto_ml import Predictor from au

Yellowbrick Visual analysis and diagnostic tools to facilitate machine learning model selection. What is Yellowbrick? Yellowbrick is a suite of visual

Rater Scoring Modeling Tool Introduction Automated scoring of written and spoken test responses is a growing field in educational natural language pro

SciKit-Learn Laboratory This Python package provides command-line utilities to make it easier to run machine learning experiments with scikit-learn. O

Master status: Development status: Package information: TPOT stands for Tree-based Pipeline Optimization Tool. Consider TPOT your Data Science Assista

"One of the holy grails of machine learning is to automate more and more of the feature engineering process." ― Pedro Domingos, A Few Useful Things to

Lale is a Python library for semi-automated data science. Lale makes it easy to automatically select algorithms and tune hyperparameters of pipelines that are compatible with scikit-learn, in a type-

pure-predict speeds up and slims down machine learning prediction applications. It is a foundational tool for serverless inference or small batch prediction with popular machine learning frameworks l

sk-dist: Distributed scikit-learn meta-estimators in PySpark What is it? sk-dist is a Python package for machine learning built on top of scikit-learn

Stochastic Gradient Trees - Python Stochastic Gradient Trees1 by Henry Gouk, Bernhard Pfahringer, and Eibe Frank implementation in Python. Based on th

Skforecast is a python library that eases using scikit-learn regressors as multi-step forecasters. It also works with any regressor compatible with the scikit-learn API (pipelines, CatBoost, LightGBM

Hello, This Notebook Contains Example of Corona Virus Tweets Multi Class Classification. - Classes is: Extremely Positive, Positive, Extremely Negativ

To-Be is a machine learning challenge on CodaLab Platform about Mortality Prediction. The challenge aims to adress the problems of medical imbalanced data classification.

Prince is a library for doing factor analysis. This includes a variety of methods including principal component analysis (PCA) and correspondence anal

Neuraxle Pipelines Code Machine Learning Pipelines - The Right Way. Neuraxle is a Machine Learning (ML) library for building machine learning pipeline

Unsupervised-Machine-Learning Flat Clustering K-Means clusternig example with Python and Scikit-learn Flat clustering Clustering algorithms group a se

An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models. Hyperactive: is very easy to lear

Algorithmic Trading This machine learning algorithm was built using Python 3 and scikit-learn with a Decision Tree Classifier. The program gathers sto

ELI5 ELI5 is a Python package which helps to debug machine learning classifiers and explain their predictions. It provides support for the following m

IMBENS: Class-imbalanced Ensemble Learning in Python Language: English | Chinese/中文 Links: Documentation | Gallery | PyPI | Changelog | Source | Downl

30-Days-of-ML-Kaggle 🔥 About the Hands On Program 💻 Machine learning beginner → Kaggle competitor in 30 days. Non-coders welcome The program starts

Welcome to sktime A unified framework for machine learning with time series We provide specialized time series algorithms and scikit-learn compatible

Welcome to sktime A unified framework for machine learning with time series We provide specialized time series algorithms and scikit-learn compatible

metric-learn: Metric Learning in Python metric-learn contains efficient Python implementations of several popular supervised and weakly-supervised met

"One of the holy grails of machine learning is to automate more and more of the feature engineering process." ― Pedro Domingos, A Few Useful Things to

PyAF (Python Automatic Forecasting) PyAF is an Open Source Python library for Automatic Forecasting built on top of popular data science python module

Clinica Software platform for clinical neuroimaging studies Homepage | Documentation | Paper | Forum | See also: AD-ML, AD-DL ClinicaDL About The Proj

Gender-classification This is a ML model to classify Male and Females using some physical characterstics Data. Python Libraries like Pandas,Numpy and

datascienv is package that helps your to setup your environment in single line of code with all dependency and it is also include pyforest that provide single line of import all required ml libraries

Regression Metrics Installation To install the package from the PyPi repository you can execute the following command: pip install regressionmetrics I

auto-sklearn auto-sklearn is an automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator. Find the documentation here

AutoML for Text, Image, and Tabular Data AutoGluon automates machine learning tasks enabling you to easily achieve strong predictive performance in yo

Orange Data Mining Orange is a data mining and visualization toolbox for novice and expert alike. To explore data with Orange, one requires no program

PlainML Painless Machine Learning Library for python based on scikit-learn. Install pip install plainml Example from plainml import KnnModel, load_ir

scikit-hts Hierarchical Time Series with a familiar API. This is the result from not having found any good implementations of HTS on-line, and my work

chainladder (python) chainladder - Property and Casualty Loss Reserving in Python This package gets inspiration from the popular R ChainLadder package

tsfeast A collection of Scikit-Learn compatible time series transformers and tools. Installation Create a virtual environment and install: From PyPi p

Modular Active Learning framework for Python3 Page contents Introduction Active learning from bird's-eye view modAL in action From zero to one in a fe

Python package for concise, transparent, and accurate predictive modeling. All sklearn-compatible and easy to use. 📚 docs • 📖 demo notebooks Modern

[Due to the time taken @ uni, work + hell breaking loose in my life, since things have calmed down a bit, will continue commiting!!!] [By the way, I'm

This is a Cricket Score Predictor that predicts the first innings score of a T20 Cricket match using Machine Learning. It is a Web Application.

Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.

Learn how to process, classify, cluster, summarize, understand syntax, semantics and sentiment of text data with the power of Python! This repository contains code and datasets used in my book, Text

A scikit-learn compatible neural network library that wraps PyTorch. Resources Documentation Source Code Examples To see more elaborate examples, look

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, A

sklearn-evaluation Machine learning model evaluation made easy: plots, tables, HTML reports, experiment tracking, and Jupyter notebook analysis. Suppo

This repository contains examples and related resources showing you how to preprocess, train, and serve your models using Amazon SageMaker with data fetched from Delta Lake.

Python Client and Toolkit for DataFrames, Big Data, Machine Learning and ETL in Elasticsearch

sports-betting sports-betting is a collection of tools that makes it easy to create machine learning models for sports betting and evaluate their perf

giotto-tda is a high-performance topological machine learning toolbox in Python built on top of scikit-learn and is distributed under the G

Use AI, Modern Portfolio Theory, and Monte Carlo simulation's to generate a optimized stock portfolio that minimizes risk while maximizing returns. Ho

Kalo dengar istilah ML, biasanya rada ambigu. Soalnya punya beberapa kepanjangan, seperti Mobile Legend, Makan Lontong, Ma**ng L*v* dan lain-lain. Tapi pada repo ini membahas Machine Learning :)

Dive into Machine Learning Hi there! You might find this guide helpful if: You know Python or you're learning it 🐍 You're new to Machine Learning You

Stacking (stacked generalization) Overview ikki407/stacking - Simple and useful stacking library, written in Python. User can use models of scikit-lea

Intel(R) Extension for Scikit-learn* Installation | Documentation | Examples | Support | FAQ With Intel(R) Extension for Scikit-learn you can accelera