1994 Open source projects that are alternatives of or similar to Data-Scientist-In-Python

PandaPy has the speed of NumPy and the usability of Pandas 10x to 50x faster (by @firmai)

Alpine Container for Machine Learning

The book was written and tested with Python 3.5, though other Python versions (including Python 2.7) should work in nearly all cases.

Heart Disease prediction using 5 algorithms

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.

Text Mining on the 2019 Mexican Government Report, covering from extracting text from a PDF file to plotting the results.

Курс "Введение в машинное обучение" (ВМК, МГУ имени М.В. Ломоносова)

For extensive instructor led learning

阿布量化交易系统(股票，期权，期货，比特币，机器学习) 基于python的开源量化交易，量化投资架构

Simple Smart Pipe: python productivity-tool for rapid data manipulation

Example PyMC3 project for performing Bayesian data analysis using a probabilistic programming approach to machine learning.

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.

Pynamical is a Python package for modeling and visualizing discrete nonlinear dynamical systems, chaos, and fractals.

A constantly updated python machine learning cheatsheet

This repository consists of all my Machine Learning Projects.

Achieve your marketing goals with the data analytics power of Python

Soomvaar is the repo which 🏩 contains different collection of 👨‍💻🚀code in Python and 💫✨Machine 👬🏼 learning algorithms📗📕 that is made during 📃 my practice and learning of ML and Python✨💥

📚 Various cheatsheets in PDF

Performance analysis of predictive (alpha) stock factors

N-D labeled arrays and datasets in Python

This repository is my attempt to help Data Science aspirants gain necessary Data Visualization skills required to progress in their career. It includes all the types of plot offered by Seaborn, applied on random datasets.

A value investing tool based on Warren Buffett, Joseph Piotroski and Benjamin Graham thoughts

텐서플로우와 머신러닝으로 시작하는 자연어처리(로지스틱회귀부터 트랜스포머 챗봇까지)

A clothing retrieval and visual recommendation model for fashion images.

Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.

A Python Matplotlib, Numpy library to manage wind data, draw windrose (also known as a polar rose plot), draw probability density function and fit Weibull distribution

Manipulate JSON-like data with NumPy-like idioms.

Bootcamp to learn Python for Machine Learning

Comet-For-MLFlow Extension

I am sharing my Journey of 66DaysofData in Natural Language Processing.

Facial Expression Recognition

No description or website provided.

단국대 SW중심대학 2020년도 오픈소스SW설계 - 캐글뽀개기 수업 일정 및 강의자료

Using Kaggle Data and Real World Data for Data Science and prediction in Python, R, Excel, Power BI, and Tableau.

Can we predict accurately on the skewed data? What are the sampling techniques that can be used. Which models/techniques can be used in this scenario? Find the answers in this code pattern!

Codice sorgente ed Errata Corrige del mio libro "A tu per tu col Machine Learning"

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.

Repository for the projects needed to complete the Data Analyst Nanodegree.

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

Recognition of Sign Language using Capsule Networks

Age classification from text using PAN16, blogs, Fisher Callhome, and Cancer Forum

Simplify your ETL processes with these hands-on data sanitation tips, tricks, and best practices

Data ETL & Analysis on the global and Mexican datasets of the COVID-19 pandemic.

Dynamic Programming implemented in Rcpp. Includes example partition and out of sample fitting applications.

DatScan is an initiative to build an open-source CMS that will have the capability to solve any problem using data Analysis just with the help of various modules and a vast standardized module library

A scalable general purpose micro-framework for defining dataflows. You can use it to create dataframes, numpy matrices, python objects, ML models, etc.

[tutorial]A functional, Data Science focused introduction to Python

Tensorflow Implementation of FaceNet: A Unified Embedding for Face Recognition and Clustering to find the celebrity whose face matches the closest to yours.

Engezny is a python package that quickly generates all possible charts from your dataframe and saves them for you, and engezny is only supporting now uni-parameter visualization using the pie, bar and barh visualizations.

datascienv is package that helps you 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

도서 "[개정판] 파이썬 라이브러리를 활용한 머신 러닝"의 주피터 노트북과 코드입니다.

SADDLE: Scala Data Library

do more with dbt. fal helps you run Python alongside dbt, so you can send Slack alerts, detect anomalies and build machine learning models.

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

2.5k code solutions with clear explanation @ onelinerhub.com

Type4Py: Deep Similarity Learning-Based Type Inference for Python

There are C language computer programs about the simulator, transformation, and test statistic of continuous Bernoulli distribution. More than that, the book contains continuous Binomial distribution and continuous Trinomial distribution.

The Fuzzy Labs guide to the universe of open source MLOps

12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools