Top Menu

Free Data Science, Analytics, Machine Learning and IoT Books

All | (Big) Data Analytics | Algorithms | Artificial Intelligence | Bayesian Networks | Business & Strategy | Computer Vision | Data Journalism | Data Mining | Data Scientists | Data Structures | Data Visualization | General Data Science | Hadoop, MapReduce | Information Retrieval | Linear Regression | Linguistic | Machine Learning, Predictive Analytics | Math | Metadata | Natural Language Processing | Network Science | Other Sites with Free Data Science Resources | Probability | Python | R | Singularity/Transhumanism | Statistics | Text Mining

Building Data Science Teams. What data scientists add to an organization, how they fit in, and how to hire and build effective data science teams
Computer Vision: Models, Learning, and Inference. A principled model-based approach to computer vision that unifies disparate algorithms, approaches, and topics under the guiding principles of probabilistic models, learning, and efficient inference algorithms
Data Mining with Weka. A collection of machine learning algorithms for data mining tasks that can either be applied directly to a dataset or called from your own Java code
Interactive Data Visualization for the Web. Visualizing data is the fastest way to communicate it to others
Data Mining: Concepts and Techniques. Concepts and techniques of data mining
Data Science with MIT Open Courseware. A choke-full of data science courses, from data mining to data visualization to social networks
A Practitioner's Guide to Generalized Linear Models. Written for the practising actuary who would like to understand generalized linear models (GLMs) and use them to analyze insurance data
Harvard Data Science Course. A fantastic series of lectures pertaining to Data Science
Big Data Analytics with Twitter. Taught in close collaboration with Twitter, focuses on the tools and algorithms for data analysis as applied to Twitter's data
Collaborative Statistics. An introductory statistics course for students majoring in fields other than engineering or math. The only prerequisite is intermediate algebra
Data Discovery for Dummies. Data discovery, what it does and how it makes dealing with big data simpler
Introduction to Data Science. A series of data problems of increasing complexity to illustrate the skills and capabilities needed by data scientists
Time Series Databases: New Ways to Store and Access Data. A new world of time series data calls for new approaches and new tools to store and access it
The Promise and Peril of Big Data. New challenges and questions facing big data: from ethics to scientific methodologies to evolution of knowledge
Data-Intensive Text Processing with MapReduce. Scalable approaches to processing large amounts of text with MapReduce
Fundamental Numerical Methods and Data Analysis. A wide range of courses that discuss numerical methods used in science
Advanced Data Analysis from an Elementary Point of View. Modern methods of data analysis and the considerations which go into choosing the right method for the job at hand
The Wealth of Networks: How Social Production Transforms Markets and Freedom. How information, knowledge and culture are produced and exchanged in our society
simpleR - Using R for Introductory Statistics. How to use R while learning introductory statistics
OpenIntro Statistics. Foundation of statistical thinking and methods
Knowledge-Oriented Applications in Data Mining. In-depth description of novel mining algorithms and many useful applications
Concepts and Applications of Inferential Statistics. A full-length and occasionally interactive statistics textbook.
Predictive Analytics for Dummies. Providing decision makers and analysts with the capability to make accurate predictions about future events based on complex statistical algorithms
New Fundamental Technologies in Data Mining. In-depth description of novel mining algorithms and many useful applications

Page 1 2 3 4 5