Displaying 1 to 20 from 120 results

Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth

  •    Python

Prophet is a procedure for forecasting time series data. It is based on an additive model where non-linear trends are fit with yearly and weekly seasonality, plus holidays. It works best with daily periodicity data with at least one year of historical data. Prophet is robust to missing data, shifts in the trend, and large outliers.Prophet is open source software released by Facebook's Core Data Science team. It is available for download on CRAN and PyPI.

knowledge-repo - A next-generation curated knowledge sharing platform for data scientists and other technical professions

  •    Python

The Knowledge Repository project is focused on facilitating the sharing of knowledge between data scientists and other technical roles using data formats and tools that make sense in these professions. It provides various data stores (and utilities to manage them) for "knowledge posts", with a particular focus on notebooks (R Markdown and Jupyter / IPython Notebook) to better promote reproducible research.Check out this Medium Post for the inspiration for the project.

Data-Analysis-and-Machine-Learning-Projects - Repository of teaching materials, code, and data for my data analysis and machine learning projects

  •    Jupyter

This is a repository of teaching materials, code, and data for my data analysis and machine learning projects.Each repository will (usually) correspond to one of the blog posts on my web site.




DataflowJavaSDK - Google Cloud Dataflow provides a simple, powerful model for building both batch and streaming parallel data processing pipelines

  •    Java

Google Cloud Dataflow SDK for Java is a distribution of Apache Beam designed to simplify usage of Apache Beam on Google Cloud Dataflow service. This artifact includes the parent POM for other Dataflow SDK artifacts.

xarray - N-D labeled arrays and datasets in Python

  •    Python

xarray (formerly xray) is an open source project and Python package that aims to bring the labeled data power of pandas to the physical sciences, by providing N-dimensional variants of the core pandas data structures. Our goal is to provide a pandas-like and pandas-compatible toolkit for analytics on multi-dimensional arrays, rather than the tabular data for which pandas excels. Our approach adopts the Common Data Model for self- describing scientific data in widespread use in the Earth sciences: xarray.Dataset is an in-memory representation of a netCDF file.

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

  •    Jupyter

This is a collection of IPython notebook/Jupyter notebooks intended to train the reader on different Apache Spark concepts, from basic to advanced, by using the Python language. If Python is not your language, and it is R, you may want to have a look at our R on Apache Spark (SparkR) notebooks instead. Additionally, if your are interested in being introduced to some basic Data Science Engineering, you might find these series of tutorials interesting. There we explain different concepts and applications using Python and R.


pachyderm - Reproducible Data Science at Scale!

  •    Go

Pachyderm is a tool for production data pipelines. If you need to chain together data scraping, ingestion, cleaning, munging, wrangling, processing, modeling, and analysis in a sane way, then Pachyderm is for you. If you have an existing set of scripts which do this in an ad-hoc fashion and you're looking for a way to "productionize" them, Pachyderm can make this easy for you. Install Pachyderm locally or deploy on AWS/GCE/Azure in about 5 minutes.

plotnine - A grammar of graphics for Python

  •    Python

plotnine is an implementation of a grammar of graphics in Python, it is based on ggplot2. The grammar allows users to compose plots by explicitly mapping data to the visual objects that make up the plot. Plotting with a grammar is powerful, it makes custom (and otherwise complex) plots easy to think about and then create, while the simple plots remain simple.

Scikit Learn - Machine Learning in Python

  •    Python

scikit-learn is a Python module for machine learning built on top of SciPy. It is simple and efficient tools for data mining and data analysis. It supports automatic classification, clustering, model selection, pre processing and lot more.

mlcourse_open - OpenDataScience Machine Learning course. Both in English and Russian

  •    Python

This is the list of published articles on medium.com 🇬🇧, habr.com 🇷🇺, and jqr.com 🇨🇳. Icons are clickable. Also, links to Kaggle Kernels (in English) are given. This way one can reproduce everything without installing a single package. Assignments will be announced each week. Meanwhile, you can pratice with demo versions. Solutions will be discussed in the upcoming run of the course.

hacknical - Hacknical, hacker & technical. A website for GitHub user to make a better resume.

  •    Javascript

A website for GitHub user to generate his GitHub data analysis (contributions/commits/languages/repos datas), helps to make a better resume. Attention:Most of the pages support English now😁😁😁, including github data analysis page.

awesome-R - A curated list of awesome R packages, frameworks and software.

  •    R

A curated list of awesome R packages and tools. Inspired by awesome-machine-learning. Packages change the way you use R.

pandas_exercises - Practice your pandas skills!

  •    Jupyter

Fed up with a ton of tutorials but no easy way to find exercises I decided to create a repo just with exercises to practice pandas. Don't get me wrong, tutorials are great resources, but to learn is to do. So unless you practice you won't learn. My suggestion is that you learn a topic in a tutorial or video and then do exercises. Learn one more topic and do exercises. If you got the answer wrong, don't go directly to the solution with code.

pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data

  •    Python

pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. Additionally, it has the broader goal of becoming the most powerful and flexible open source data analysis / manipulation tool available in any language. It is already well on its way toward this goal. Binary installers for the latest released version are available at the Python package index and on conda.