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北美+德国18名校的数据挖掘、数据分析、人工智能及机器学习课程资源汇总
2月 17th, 2013
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What is Data Science?
How do I become a Data Scientist?
How does Data Science differ from traditional statistical analysis?
Related Courses
Concepts in Computing with Data, Berkeley
Practical Machine Learning, Berkeley
Artificial Intelligence, Berkeley
Visualization, Berkeley
Data Mining and Analytics in Intelligent Business Services, Berkeley
Data Science and Analytics: Thought Leaders, Berkeley
Machine Learning, Stanford
Paradigms for Computing with Data, Stanford
Mining Massive Data Sets, Stanford
Data Visualization, Stanford
Algorithms for Massive Data Set Analysis, Stanford
Research Topics in Interactive Data Analysis, Stanford
Data Mining, Stanford
Machine Learning, CMU
Statistical Computing, CMU
Machine Learning with Large Datasets, CMU
Machine Learning, MIT
Data Mining, MIT
Statistical Learning Theory and Applications, MIT
Data Literacy, MIT
Introduction to Data Mining, UIUC
Learning from Data, Caltech
Introduction to Statistics, Harvard
Data-Intensive Information Processing Applications, University of Maryland
Dealing with Massive Data, Columbia
Data-Driven Modeling, Columbia
Introduction to Data Mining and Analysis, Georgia Tech
Computational Data Analysis: Foundations of Machine Learning and Da…, Georgia Tech
Applied Statistical Computing, Iowa State
Data Visualization, Rice
Data Warehousing and Data Mining, NYU
Data Mining in Engineering, Toronto
Machine Learning and Data Mining, UC Irvine
Knowledge Discovery from Data, Cal Poly
Large Scale Learning, University of Chicago
Data Science: Large-scale Advanced Data Analysis, University of Florida
Strategies for Statistical Data Analysis, Universität Leipzig
Related Workshops
Data Bootcamp, Strata 2011
Machine Learning Summer School, Purdue 2011
Looking at Data
Books
Competing on Analytics
Analytics at Work
Super Crunchers
The Numerati
Data Driven
Data Source Handbook
Programming Collective Intelligence
Mining the Social Web
Data Analysis with Open Source Tools
Visualizing Data
The Visual Display of Quantitative Information
Envisioning Information
Visual Explanations: Images and Quantities, Evidence and Narrative
Beautiful Evidence
Think Stats
Data Analysis Using Regression and Multilevel/Hierarchical Models
Applied Longitudinal Data Analysis
Design of Observational Studies
Statistical Rules of Thumb
All of Statistics
A Handbook of Statistical Analyses Using R
Mathematical Statistics and Data Analysis
The Elements of Statistical Learning
Counterfactuals and Causal Inference
Mining of Massive Data Sets
Data Analysis: What Can Be Learned From the Past 50 Years
Bias and Causation
Regression Modeling Strategies
Probably Not
Statistics as Principled Argument
The Practice of Data Analysis
Videos
Lies, damned lies and statistics (about TEDTalks)
The Joy of Stats
Journalism in the Age of Data
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