7866 Open source projects that are alternatives of or similar to Zat

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

Code, Notebooks and Examples from Practical Business Python

Open Machine Learning Course

A collection of notebooks of my Machine Learning class written in python 3

For extensive instructor led learning

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 Case Study Approach to Successful Data Science Projects Using Python, Pandas, and Scikit-Learn

My dataquest project solutions

Association Rule Mining from Spatial Data for Crime Analysis

Apache Spark & Python (pySpark) tutorials for Big Data Analysis and Machine Learning as IPython / Jupyter notebooks

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.

主要是爬虫与数据分析项目总结，外加建模与机器学习，模型的评估。

Material for my PyData Jupyter & Pandas Workshops, I'm also available for personal in-house trainings on request

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.

HandySpark - bringing pandas-like capabilities to Spark dataframes

🎓 Jupyter notebooks from UFC data science course

Portfolio of data science projects completed by me for academic, self learning, and hobby purposes.

Practice your pandas skills!

Alpine Container for Machine Learning

🚚 Agile Data Preparation Workflows made easy with dask, cudf, dask_cudf and pyspark

Credit Risk analysis by using Python and ML

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

Jupyter notebook and datasets from the pandas Q&A video series

100 data puzzles for pandas, ranging from short and simple to super tricky (60% complete)

Data Science Hacks consists of tips, tricks to help you become a better data scientist. Data science hacks are for all - beginner to advanced. Data science hacks consist of python, jupyter notebook, pandas hacks and so on.

Visualizer for pandas data structures

Compilation of R and Python programming codes on the Data Professor YouTube channel.

Type System for Data Analysis in Python

Disease Prediction based on Symptoms.

50% faster, 50% less RAM Machine Learning. Numba rewritten Sklearn. SVD, NNMF, PCA, LinearReg, RidgeReg, Randomized, Truncated SVD/PCA, CSR Matrices all 50+% faster

📚 Various cheatsheets in PDF

Feature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering can be considered as applied machine learning itself.

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

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

利用Python进行数据分析 第二版 (2017) 中文翻译笔记

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

Create HTML profiling reports from pandas DataFrame objects

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, AWS, and various command lines.

brief introduction to Python 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.

Data Science & Machine Learning projects and tutorials in python from beginner to advanced level.

🛠 All-in-one web-based IDE specialized for machine learning and data science.

edaviz - Python library for Exploratory Data Analysis and Visualization in Jupyter Notebook or Jupyter Lab

Kaggle Struggle

Tools that make working with scikit-learn and pandas easier.

A Los Angeles Times analysis of Every shot in Kobe Bryant's NBA career

open source for wechat-official-account (ID: PyDataLab)

Algorithmic trading using machine learning.

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

Machine Learning for Spot Prices

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

API for manipulating time series on top of Apache Spark: lagged time values, rolling statistics (mean, avg, sum, count, etc), AS OF joins, downsampling, and interpolation

Jupyter notebooks from the scikit-learn video series

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

Stock for Deep Learning and Machine Learning

data wrangling simplicity, complete audit transparency, and at speed

A guide to getting started with Data Science and ML.

Notes and tutorials on how to use python, pandas, seaborn, numpy, matplotlib, scipy for data science.

Short programming tutorials pertaining to data analysis.

What's in your data? Extract schema, statistics and entities from datasets