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

SQL School by Mode Analytics. Made up of 2 modules: a) SQL skill building b) Analytics training - learning to think like an analyst
Field Guide to Hadoop. An introduction to Hadoop, its ecosystem and aligned technologies
Business Analytics in Retail for Dummies. Using business analytics to discover insights that, when acted on, drive revenue growth and improve customer relations
Big Data Now: Current Perspective from O'Reilly Media. Top big data posts from late fall 2012 through late fall 2013
What is Data Science?. A book on data science and how it enables the creation of data products
An Introduction to R. R is an integrated suite of software facilities for data manipulation, calculation and graphical display
Data Science: An Introduction by Wikibooks. Basic introduction to data science designed for the advanc ed high school student or average college freshman
Modeling with Data: Tools and Techniques for Scientific Computing. Executing computationally intensive analyses on very large data sets
Network Science. Concepts of network science and the tools that can be used to study real networks and interpret the obtained results
Applied Data Science. Taking people with strong mathematical / statistical knowledge and teaching them software development fundamentals
Analyzing Linguistic Data: A practical introduction to statistics. Statistical analysis of language, designed for linguists with a non-mathematical background
Think Stats: Probability and Statistics for Beginners. Emphasizes the use of statistics and a computational approach to explore large datasets
Statistics with R. Notes author took while discovering and using the statistical environment R
R and Data Mining: Examples and Case Studies. Various data mining functionalities in R and three case studies of real world applications
Analyzing the Analyzers: An introspective survey of data scientists and their work. Survey of several hundred data science practitioners in mid-2012
Mining of Massive Datasets. Data mining of very large amounts of data, that is, data so large it does not fit in main memory
An Introduction to Information Retrieval. Scientific underpinnings of information retrieval
A Course in Machine Learning. Covers most major aspects of modern machine learning
Probabilistic Programming & Bayesian Methods for Hackers. Intro to Bayesian methods and probabilistic programming
The Field Guide to Data Science. Appreciating the insights data can provide us today
Information Theory, Inference, and Learning Algorithms. Bayesian data modelling, Monte Carlo methods, variational methods, clustering algorithms, and neural networks
Introduction to Probability. Introductory probability course
Data+Design: A simple introduction to preparing and visualizing information. The actual set of steps that need to be accomplished before data can be visualized, from the design of the survey to the collection of the data to ultimately its visualization
An Introduction to Data Mining. A creative way of learning about data mining
Data Science with CMU's Open Learning Initiative. As of today, the only data science related MOOCs offered by CMU's Open Learning Initiative are those related to statistics
Natural Language Processing with Python. A book about Natural Language Processing
Codecademy: Python. An interactive "Python for Beginners" tutorial that allows you to code while learning the fundamentals
Data Science and Cognitive Computing Courses. Build Data Science and Cognitive Computing skills for free today
Big Data Analytics Infrastructure for Dummies. The emphasis is on hardware infrastructure - processing, storage, systems software, and internal networks
The Elements of Statistical Learning (Data Mining, Inference and Prediction). Bringing together many new ideas in learning and explaining them in a statistical framework
Disruptive Possibilities: How Big Data Changes Everything. Evolution of commodity supercomputing and the simplicity of big data technology, to the ways conventional clouds differ from Hadoop analytics clouds
Free Data Science Books from Intech. Lots of Data Science books you can read online. Search for them using keywords like data science, data mining, machine learning, etc
An Introduction to Statistical Learning (with applications in R). For those wishing to use statistical learning tools to analyze their data
Real-Time Big Data Analytics: Emerging Architecture. Using real-time big data analytics (RTBDA) to improve sales, lower costs a ticket to improved sales, higher profits and lower marketing costs
The Evolution of Data Products. Discusses what happens when data becomes a product, specifically, a consumer product, and where these data products headed
Introduction to Social Network Methods. Building an understanding of a social network with complete and rigorous descriptions of social relationship patterns
Networks, Crowds & Markets: Reasoning about a highly connected world. Links that connect us and the ways in which each of our decisions can have subtle consequences for the outcomes of everyone else
Forecasting: principles and practice. Comprehensive introduction to forecasting methods
Introduction to Metadata. Overview of metadata and its current trends, especially that of metadata created by users
Statistics by Modern statistics and some practical applications of statistics
Data Mining and Analysis: Fundamental Concepts and Algorithms. Fundamental algorithms in data mining and analysis that form the basis for the emerging field of data science
Introduction to Statistical Thought. A focus on ideas that statisticians care about as opposed to technical details of how to put those ideas into practice
Theory and Applications for Advanced Text Mining. Advanced text mining techniques
Data Mining and Knowledge Discovery in Real Life Applications. Four different ways of theoretical and practical advances and applications of data mining in different promising areas like Industrialist, Biological, and Social
Introduction to Machine Learning. Very comprehensive overview of machine learning
A First Encounter with Machine Learning. A first read to wet the appetite so to speak, a prelude to the more advanced machine learning topics
Gaussian Processes for Machine Learning. One of the most important Bayesian machine learning approaches
Practical Machine Learning: Innovations in Recommendations. Innovations that make machine learning practical for business production settings
Interactive Data Visualization for the Web. Dynamic, interactive visualizations to empower people to explore the data for themselves
A Programmer's Guide to Data Mining. Tool for learning basic data mining techniques

Page 1 2 3 4 5