/awesome-datascience

An awesome Data Science repository to learn and apply for real world problems.

MIT LicenseMIT

Awesome Data Science

An open source DataScience repository to learn and apply for real world problems.

Motivation

This part for dummies who are new on Data Science

This is shortcut path to start studying on Data Science . Just follow steps to understand "What is Data Science and What should study to learn Data Science?"

First of all, Data Science is hottest topic on Computer and Internet farmland nowadays. People have created pretty much data from applications and systems until today and now time to analyze them. The next steps are producing suggestions from these data and creating predictions about future. You can find here biggest question for DataScience ever and hundreds of answers from experts. Our favorite data scientist is Clare Corthell. She is expert of data related systems and hacker, now she has been working on a company as a DataScientist. Clara's blog. This web site helps you to understand exact way to study as a professional data scientist.

Secondly, Our favorite programming language is Python nowadays for #DataScience. Because Python - Pandas library have fully functionality collecting data and analyzing. We use Anaconda to play data and to create applications.

This is the guide Guide to begin a DataScience project.

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Swami Chandrasekaran make a Curriculum via Metro map.

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by @gwenthomasdgi via twitter

What is Data Science?

MOOC's

Data Sets

Bloggers

Facebook Accounts

Twitter Accounts

  • Wes McKinney - Pandas (Python Data Analysis library).
  • Matthew Russell - Mining the Social Web.
  • Greg Reda Working @ GrubHub about data and pandas
  • Kevin Davenport - Organizer of http://sddatascience.com
  • Julia Evans - Hacker - Pandas - Data Analyze
  • Hakan Kardas - Data Scientist
  • Big Data Science - Big Data, Data Science, Predictive Modeling, Business Analytics, Hadoop, Decision and Operations Research.
  • Ryan Orban - Data scientist, genetic origamist, hardware aficionado
  • Sean J. Taylor - Social Scientist. Hacker. Facebook Data Science Team. Keywords: Experiments, Causal Inference, Statistics, Machine Learning, Economics.
  • Drew Conway - Data nerd, hacker, student of conflict.
  • Data Science Central - Data Science Central is the industry's single resource for Big Data practitioners.
  • Hilary Mason - Data Scientist in Residence at @accel.
  • Juan Miguel Lavista - Principal Data Scientist @ Microsoft Data Science Team
  • Data Science Tips - Tips and Tricks for Data Scientists around the world! #datascience #bigdata
  • Erin Bartolo - Running with #BigData--enjoying a love/hate relationship with its hype. @iSchoolSU #DataScience Program Mgr.
  • Noah Iliinsky - Visualization & interaction designer. Practical cyclist. Author of vis books: http://www.oreillynet.com/pub/au/4419
  • Matt Harrison - Opinions of full-stack Python guy, author, instructor, currently playing Data Scientist. Occasional fathering, husbanding, ult|goalt-imate, organic gardening.
  • Data Science Renee - Documenting my path from SQL Data Analyst pursuing an Engineering Master's Degree to Data Scientist
  • Vamshi Ambati - Data Science @ PayPal. #NLP, #machinelearning; PhD, Carnegie Mellon alumni (Blog: http://allthingsds.wordpress.com )
  • Tony Ojeda - Data Scientist | Author | Entrepreneur. Co-founder @DataCommunityDC. Founder @DistrictDataLab. #DataScience #BigData #DataDC
  • Prash Chan - Solution Architect @ IBM, Master Data Management, Data Quality & Data Governance Blogger. Data Science, Hadoop, Big Data & Cloud.
  • Clare Corthell - Dev, Design, Data Science @mattermark #hackerei
  • Paul Miller - Cloud Computing/ Big Data/ Open Data Analyst & Consultant. Writer, Speaker & Moderator. Gigaom Research Analyst.
  • Data Science London Data Science. Big Data. Data Hacks. Data Junkies. Data Startups. Open Data
  • dj patil Applying data science to decision making. VP @RelateIQ
  • Gregory Piatetsky - KDnuggets President, Analytics/Big Data/Data Mining/Data Science expert, KDD & SIGKDD co-founder, was Chief Scientist at 2 startups, part-time philosopher.
  • Peter Skomoroch - Creating intelligent systems to automate tasks & improve decisions. Entrepreneur, ex Principal Data Scientist @LinkedIn. Machine Learning, ProductRei, Networks
  • Monica Rogati - Data @ Jawbone. Turned data into stories & products at LinkedIn. Text mining, applied machine learning, recommender systems. Ex-gamer, ex-machine coder; namer.
  • Jeff Hammerbacher ReTweeting about data science
  • John Myles White Scientist at Facebook and Julia developer. Author of Machine Learning for Hackers and Bandit Algorithms for Website Optimization. Tweets reflect my views only.
  • Quora Data Science Quora's data science topic
  • Data Science Report - Mission is to help guide & advance careers in Data Science & Analytics
  • Luis Rei - PhD Student. Programming, Mobile, Web. Artificial Intelligence, Intelligent Robotics Machine Learning, Data Mining, Natural Language Processing, Data Science.
  • Spencer Nelson - Data nerd
  • Recep Erol - Data Science geek @ Rice University
  • DataScienceX
  • Talha Oz - Enjoys ABM, SNA, DM, ML, NLP, HI, Python, Java. Top percentile kaggler/data scientist
  • Rand Hindi
  • Big Data Combine - Rapid-fire, live tryouts for data scientists seeking to monetize their models as trading strategies
  • Tony Baer - IT analyst with Ovum covering Big Data & data management with some systems engineering thrown in.
  • Domino Data Lab
  • Terry Timko - InfoGov; Bigdata; Data as a Service; Data Science; Open, Social & Business Data Convergence
  • Big Data Mania - Data Viz Wiz | Data Journalist | Growth Hacker | Author of Data Science for Dummies (2015)
  • Chris Said - Data scientist at Twitter
  • WileyEd - Senior Manager - @Seagate Big Data Analytics | @McKinsey Alum | #BigData + #Analytics Evangelist | #Hadoop, #Cloud, #Digital, & #R Enthusiast
  • Tasos Skarlatidis - Complex Event Processing, Big Data, Artificial Intelligence and Machine Learning. Passionate about programming and open-source.
  • Mark Stevenson - Data Analytics Recruitment Specialist at Salt (@SaltJobs) | Analytics - Insight - Big Data - Datascience
  • Data Vizzard - DataViz, Security, Military
  • Machine Learning - Live Content Curated by top 1K Machine Learning Experts
  • Charlie Greenbacker - Director of Data Science at @ExploreAltamira
  • Emilio Ferrara - #Networks, #MachineLearning and #DataScience. I work on #Social Media. Postdoc at @IndianaUniv
  • WNYC Data News Team - The data news crew at @WNYC. Practicing data-driven journalism, making it visual and showing our work.
  • TextDataMiningReddit
  • Silvia K. Spiva - #DataScience at Cisco
  • DADI Charles-Abner - #datascientist @Ekimetrics. , #machinelearning #dataviz #DynamicCharts #Hadoop #R #Python #NLP #Bitcoin #dataenthousiast
  • Kim Rees - Interactive data visualization and tools. Data flaneur.

Toolboxes - Environment

  • Hortonworks Sandbox is a personal, portable Hadoop environment that comes with a dozen interactive Hadoop tutorials.
  • R is a free software environment for statistical computing and graphics.
  • Python - Pandas - Anaconda Completely free enterprise-ready Python distribution for large-scale data processing, predictive analytics, and scientific computing
  • Scikit-Learn Machine Learning in Python
  • Data Science Toolbox - Coursera Course
  • Data Science Toolbox - Blog
  • Wolfram Data Science Platform Take numerical, textual, image, GIS or other data and give it the Wolfram treatment, carrying out a full spectrum of data science analysis and visualization and automatically generating rich interactive reports—all powered by the revolutionary knowledge-based Wolfram Language.
  • Sense Data Science Development Paltform A New Cloud Platform for Data Science and Big Data Analytics Collaborate on, scale, and deploy data analysis and advanced analytics projects radically faster. Use the most powerful tools — R, Python, JavaScript, Redshift, Hive, Impala, Hadoop, and more — supercharged and integrated in the cloud.
  • Mortardata Solutions, code, and devops for high-scale data science.
  • Variance Build powerful data visualizations for the web without writing JavaScript
  • Kite Development Kit The Kite Software Development Kit (Apache License, Version 2.0), or Kite for short, is a set of libraries, tools, examples, and documentation focused on making it easier to build systems on top of the Hadoop ecosystem.
  • Domino Data Labs Run, scale, share, and deploy your models — without any infrastructure or setup.
  • Apache Flink A platform for efficient, distributed, general-purpose data processing.
  • Apache Hama Apache Hama is an Apache Top-Level open source project, allowing you to do advanced analytics beyond MapReduce.
  • Weka Weka is a collection of machine learning algorithms for data mining tasks.
  • Octave GNU Octave is a high-level interpreted language, primarily intended for numerical computations.(Free Matlab)

Presentations

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