The Art of Data Science Roger Peng Pdf Free Download
4.ii (352 Ratings)
Bogus Intelligence
Bogus Intelligence A Mod Approach, 1st Edition
Comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. Number one in its field, this textbook is platonic for 1 or two-semester, undergraduate or graduate-level courses in Artificial Intelligence.
iv.0 (18 Ratings)
Artificial Intelligence
Learning Deep Architectures for AI
Foundations and Trends(r) in Car Learning.
3.5 (ii Ratings)
Artificial Intelligence
The LION Fashion: Machine Learning plus Intelligent Optimization
Learning and Intelligent Optimization (LION) is the combination of learning from data and optimization applied to solve complex and dynamic problems. Learn about increasing the automation level and connecting data directly to decisions and actions.
3.5 (116 Ratings)
Big Data
Disruptive Possibilities: How Large Data Changes Everything
This book provides an historically-informed overview through a wide range of topics, from the development of commodity supercomputing and the simplicity of big data technology, to the ways conventional clouds differ from Hadoop analytics clouds.
4.2 (116 Ratings)
Information science Topics
Computer Vision
Challenging real-world applications where vision is being successfully used, both for specialized applications such as medical imaging, and for fun, consumer-level tasks such as image editing and stitching, which you lot can utilize on you ain personal media
Languages: Python
iv.i (473 Ratings)
Information science Topics
Natural Language Processing with Python
This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and electronic mail filtering to automatic summarization and translation.
Languages: Python
4.0 (50 Ratings)
Reckoner Science Topics
Programming Computer Vision with Python
If you desire a bones agreement of computer vision's underlying theory and algorithms, this easily-on introduction is the ideal place to get-go. You'll learn techniques for object recognition, 3D reconstruction, stereo imaging, augmented reality, etc
3.7 (175 Ratings)
Data Assay
The Elements of Information Analytic Style
Data analysis is at least equally much art as it is scientific discipline. This volume is focused on the details of data analysis that sometimes autumn through the cracks in traditional statistics classes and textbooks.
Data Mining and Machine Learning
A Course in Machine Learning
Data Mining and Machine Learning
A First Run across with Machine Learning
four.1 (5 Ratings)
Data Mining and Machine Learning
Algorithms for Reinforcement Learning
This book gives a very quick merely yet thorough introduction to reinforcement learning, and includes algorithms for quite a few methods. This is everything a graduate educatee could ask for in a text.
Data Mining and Machine Learning
A Programmer's Guide to Data Mining
A guide to practical information mining, collective intelligence, and building recommendation systems by Ron Zacharski. This work is licensed under a Creative Commons license.
iv.1 (169 Ratings)
Data Mining and Machine Learning
Bayesian Reasoning and Machine Learning
For last-year undergraduates and master'southward students with limited background in linear algebra and calculus. Comprehensive and coherent, information technology develops everything from bones reasoning to advanced techniques within the framework of graphical models.
Languages: R
Data Mining and Auto Learning
Data Mining Algorithms In R
4.ii (12 Ratings)
Data Mining and Automobile Learning
Data Mining and Analysis: Central Concepts and Algorithms
The chief parts of the volume include exploratory data assay, pattern mining, clustering, and classification. The volume lays the bones foundations of these tasks, and also covers many more cutting-edge data mining topics.
iii.9 (159 Ratings)
Data Mining and Auto Learning
Data Mining: Practical Automobile Learning Tools and Techniques
Offers a thorough grounding in motorcar learning concepts as well every bit practical advice on applying auto learning tools and techniques in existent-world data mining situations.
Languages: R
four.1 (36 Ratings)
Data Mining and Machine Learning
Data Mining with Rattle and R
This volume aims to get you into data mining chop-chop. Load some data (east.thousand., from a database) into the Rattle toolkit and within minutes y'all will have the data visualised and some models built.
Data Mining and Motorcar Learning
Deep Learning
The Deep Learning textbook is a resource intended to help students and practitioners enter the field of machine learning in general and deep learning in particular.
four.two (87 Ratings)
Information Mining and Machine Learning
Gaussian Processes for Machine Learning
A comprehensive and cocky-contained introduction to Gaussian processes, which provide a principled, practical, probabilistic arroyo to learning in kernel machines.
4.5 (421 Ratings)
Data Mining and Machine Learning
Information Theory, Inference, and Learning Algorithms
"Essential reading for students of electric engineering and estimator science; also a neat heads-up for mathematics students concerning the subtlety of many commonsense questions." Choice
Data Mining and Machine Learning
Introduction to Car Learning
Data Mining and Machine Learning
Introduction to Car Learning
Data Mining and Machine Learning
KB – Neural Information Mining with Python Sources
Information Mining and Auto Learning
Car Learning
2.nine (1 Ratings)
Data Mining and Automobile Learning
Machine Learning, Neural and Statistical Classification
Data Mining and Machine Learning
Machine Learning – The Consummate Guide
4.3 (24 Ratings)
Data Mining and Machine Learning
Mining of Massive Datasets
Essential reading for students and practitioners, this book focuses on practical algorithms used to solve key issues in data mining, with exercises suitable for students from the advanced undergraduate level and beyond.
Information Mining and Automobile Learning
Modeling With Information
Modeling with Data offers a useful blend of data-driven statistical methods and nuts-and-bolts guidance on implementing those methods. --Pat Hall, founder of Translation Creation
Information Mining and Machine Learning
Neural Networks and Deep Learning
Neural networks and deep learning currently provide the best solutions to many issues in image recognition, speech recognition, and natural language processing. This volume will teach yous concepts backside neural networks and deep learning.
Languages: Python
4.0 (151 Ratings)
Information Mining and Motorcar Learning
Probabilistic Programming & Bayesian Methods for Hackers
illuminates Bayesian inference through probabilistic programming with the powerful PyMC linguistic communication and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you tin can achieve effective solutions in small-scale increments.
Data Mining and Auto Learning
Existent-Earth Active Learning
Applications and Strategies for Human-in-the-loop Machine Learning.
iv.v (450 Ratings)
Information Mining and Machine Learning
Reinforcement Learning: An Introduction
A articulate and elementary account of the primal ideas and algorithms of reinforcement learning. Their give-and-take ranges from the history of the field's intellectual foundations to the most contempo developments and applications.
4.1 (1 Ratings)
Data Mining and Automobile Learning
Social Media Mining An Introduction
Suitable for use in advanced undergraduate and outset graduate courses also as professional short courses, the text contains exercises of unlike degrees of difficulty that improve agreement and help apply concepts in social media mining
Data Mining and Machine Learning
Theory and Applications for Advanced Text Mining
This book is equanimous of 9 chapters introducing advanced text mining techniques. They are diverse techniques from relation extraction to nether or less resourced language.
4.two (86 Ratings)
Data Mining and Motorcar Learning
Understanding Car Learning: From Theory to Algorithms
The aim of this textbook is to introduce car learning, and the algorithmic paradigms it offers, in a principled way.
4.0 (3 Ratings)
Data Science in General
An Introduction to Information Science
This volume was developed for the Certificate of Information Science pro- gram at Syracuse Academy's School of Data Studies.
iii.viii (217 Ratings)
Data Science in General
Data Jujitsu: The Art of Turning Data into Product
Acquire how to use a problem'south "weight" confronting itself. Learn more almost the problems before starting on the solutions—and use the findings to solve them, or determine whether the problems are worth solving at all.
Data Science in General
School of Data Handbook
The School of Data Handbook is a companion text to the School of Information. Its part is something like a traditional textbook – it will provide the detail and background theory to support the School of Data courses and challenges.
3.vii (12 Ratings)
Information Science in General
The Art of Information Scientific discipline
This book describes the process of analyzing data. The authors take extensive experience both managing data analysts and conducting their ain data analyses, and this book is a distillation of their feel...
Languages: JavaScript
three.9 (8 Ratings)
Data Visualization
D3 Tips and Tricks
D3 Tips and Tricks is a book written to assist those who may exist unfamiliar with JavaScript or web page cosmos get started turning data into visualization.
4.ane (424 Ratings)
Information Visualization
Interactive Data Visualization for the Web
Create and publish your own interactive data visualization projects on the Spider web—even if you have little or no feel with data visualization or web development. It's easy and fun with this applied, hands-on introduction.
iv.ane (27 Ratings)
Distributed Computing Tools
Data-Intensive Text Processing with MapReduce
MapReduce [45] is a programming model for expressing distributed computations on massive amounts of data and an execution framework for large-scale data processing on clusters of commodity servers. Information technology was originally developed past Google...
Distributed Computing Tools
Hadoop Illuminated
'Hadoop illuminated' is the open source volume almost Apache Hadoop™. It aims to make Hadoop cognition accessible to a wider audition, not but to the highly technical.
Distributed Computing Tools
Hadoop Tutorial as a PDF
Intro to Hadoop - An open-source framework for storing and processing large information in a distributed environment across clusters of computers using simple programming models. Information technology is designed to scale up from single servers to thousands of machines.
iii.6 (53 Ratings)
Distributed Calculating Tools
Programming Grunter
This guide is an ideal learning tool and reference for Apache Pig, the open source engine for executing parallel data flows on Hadoop.
iii.6 (320 Ratings)
Forming Data Science Teams
Building Information Science Teams
In this in-depth study, data scientist DJ Patil explains the skills,perspectives, tools and processes that position data science teams for success.
3.8 (352 Ratings)
Forming Information Science Teams
Information Driven: Creating a Data Civilisation
In this O'Reilly report, DJ Patil and Hilary Mason outline the steps yous demand to accept if your company is to be truly data-driven—including the questions you should ask and the methods yous should prefer.
4.0 (37 Ratings)
Interviews with Data Scientists
The Data Science Handbook
The Data Science Handbook is a compilation of in-depth interviews with 25 remarkable data scientists, where they share their insights, stories, and advice.
Languages: Python
4.1 (23 Ratings)
Learning Languages
A Byte of Python
'A Byte of Python' is a free book on programming using the Python language. It serves every bit a tutorial or guide to the Python language for a beginner audience. If all you know virtually computers is how to save text files, then this is the book for you.
Languages: R
iv.5 (223 Ratings)
Learning Languages
Advanced R
Useful tools and techniques for attacking many types of R programming issues, helping you avoid mistakes and expressionless ends. With ten+ years of experience programming in R, the writer illustrates the elegance, dazzler, and flexibility at the eye of R.
Languages: R
Learning Languages
A Little Book of R for Time Series
This is a elementary introduction to time series analysis using the R statistics software.
Languages: Python
4.3 (1884 Ratings)
Learning Languages
Automate the Boring Stuff with Python: Applied Programming for Total Beginners
Practical programming for total beginners. In Automate the Boring Stuff with Python, you'll learn how to use Python to write programs that do in minutes what would accept yous hours to practice by hand-no prior programming experience required.
Languages: Python
iii.8 (260 Ratings)
Learning Languages
Dive Into Python 3
This is a hands-on guide to Python 3 and its differences from Python 2. Each chapter starts with a existent, complete lawmaking sample, picks it apart and explains the pieces, and then puts it all back together in a summary at the stop.
Languages: R
4.two (38 Ratings)
Learning Languages
Ecological Models and Data in R
The showtime truly practical introduction to modern statistical methods for ecology. In stride-past-step item, the volume teaches ecology graduate students and researchers everything they need to know to clarify their own data using the R language.
Languages: Python
4.one (130 Ratings)
Learning Languages
Invent with Python
"Invent Your Own Estimator Games with Python" teaches you figurer programming in the Python programming linguistic communication. Each affiliate gives yous the consummate source code for a new game and teaches the programming concepts from these examples.
Languages: R
Learning Languages
Learning Statistics with R
I (Dani) started teaching the introductory statistics class for psychology students offered at the University of Adelaide, using the R statistical package as the primary tool. These are my own notes for the course which were trans-coded to book form.
Languages: Python
4.i (14 Ratings)
Learning Languages
Learning with Python 3
Introduction to calculator science using the Python programming language. It covers the basics of computer programming in the kickoff part while later capacity cover basic algorithms and data structures.
Languages: Python
4.0 (nine Ratings)
Learning Languages
Learn Python, Break Python
This is a hands-on introduction to the Python programming language, written for people who have no experience with programming whatsoever. After all, everybody has to start somewhere.
Languages: Python
3.9 (136 Ratings)
Learning Languages
Larn Python the Hard Way
This is a costless sample of Learn Python 2 The Difficult Manner with 8 exercises and Appendix A available for you to review.
Languages: R
Learning Languages
Applied Regression and Anova using R
This book is Non introductory. The emphasis of this text is on the do of regression and analysis of variance. The objective is to learn what methods are available and more importantly, when they should be applied.
Languages: Python
4.3 (449 Ratings)
Learning Languages
Python for Everybody
This book is designed to introduce students to programming and computational thinking through the lens of exploring data. You can remember of Python as your tool to solve bug that are far beyond the capability of a spreadsheet.
Languages: Python
Learning Languages
Python for You and Me
This is a simple book to learn the Python programming language, it is for the programmers who are new to Python.
Languages: Python
Learning Languages
Python Practise Book
This volume is prepared from the training notes of Anand Chitipothu.
Languages: Python
Learning Languages
Python Programming
This volume describes Python, an open-source general-purpose interpreted programming language bachelor for a broad range of operating systems. This volume describes primarily version 2, but does at times reference changes in version 3.
Languages: R
Learning Languages
R past Example
Languages: R
Learning Languages
R Programming
The aim of this Wikibook is to exist the place where anyone can share his or her knowledge and tricks on R. It is supposed to be organized by task only not past discipline. We try to make a cross-disciplinary book, i.e. a volume that can be used by all.
Languages: R
Learning Languages
R Programming for Data Science
This book is nearly the fundamentals of R programming. Y'all will get started with the basics of the language, learn how to dispense datasets, how to write functions, and how to debug and optimize code.
Languages: R
Learning Languages
Spatial Epidemiology Notes: Applications and Vignettes in R
My intent is to present a relatively cursory, non-jargony overview of how practicing epidemiologists can apply some of the extremely powerful spatial analytic tools that are hands bachelor to them.
Languages: R
4.0 (vii Ratings)
Learning Languages
The R Inferno
An essential guide to the trouble spots and oddities of R. In spite of the quirks exposed here, R is the best computing environment for near data assay tasks.
Languages: R
Learning Languages
The R Manuals
The R Manuals.
Languages: Python
four.1 (75 Ratings)
Learning Languages
Think Python 2d Edition
This easily-on guide takes you through Python a step at a fourth dimension, offset with bones programming concepts before moving on to functions, recursion, data structures, and object-oriented design. Updated to Python 3.
3.7 (2 Ratings)
Math Topics
A First Class in Linear Algebra
This is an introduction to the basic concepts of linear algebra, forth with an introduction to the techniques of formal mathematics. Information technology has numerous worked examples, exercises and complete proofs, ideal for independent study.
4.2 (24 Ratings)
Math Topics
Elementary Practical Topology
This text gives a brisk and engaging introduction to the mathematics backside the recently established field of Applied Topology.
4.5 (6 Ratings)
Math Topics
Unproblematic Differential Equations
This text has been written in articulate and authentic linguistic communication that students tin can read and comprehend. The author has minimized the number of explicitly state theorems and definitions, in favor of dealing with concepts in a more than conversational fashion.
4.3 (thirteen Ratings)
Math Topics
Introduction to Probability
This book is designed for an introductory probability course at the university level for sophomores, juniors, and seniors in mathematics, physical and social sciences, engineering, and computer science.
Math Topics
Linear Algebra
Math Topics
Linear Algebra: An Introduction to Mathematical Soapbox
3.5 (1 Ratings)
Math Topics
Linear Algebra, Theory And Applications
This book gives a cocky- independent treatment of linear algebra with many of its most important applications. It is very unusual if not unique in existence an unproblematic book which does not neglect capricious fields of scalars and the proofs of the theorems
Math Topics
Ordinary Differential Equations
Math Topics
Probabilistic Models in the Report of Linguistic communication
Math Topics
Probability and Statistics Cookbook
The probability and statistics cookbook is a succinct representation of various topics in probability theory and statistics. It provides a comprehensive mathematical reference reduced to its essence, rather than aiming for elaborate explanations.
Languages: Cassandra
SQL, NoSQL, and Databases
Cassandra Tutorial as a PDF
Languages: NoSQL
SQL, NoSQL, and Databases
Extracting Data from NoSQL Databases
Languages: Graph DB
three.6 (22 Ratings)
SQL, NoSQL, and Databases
Graph Databases
Get started with O'Reilly'due south Graph Databases and observe how graph databases can assistance you lot manage and query highly continued data.
Languages: NoSQL
SQL, NoSQL, and Databases
NoSQL Databases
Languages: SQL
SQL, NoSQL, and Databases
SQL for Web Nerds
Languages: SQL
SQL, NoSQL, and Databases
SQL Tutorial as a PDF
This tutorial volition give you a quick start to SQL. It covers most of the topics required for a basic understanding of SQL and to go a experience of how it works.
Languages: MongoDB
SQL, NoSQL, and Databases
The Lilliputian MongoDB Book
MongoDB is an open source NoSQL database, easily scalable and high performance. It retains some similarities with relational databases which, in my opinion, makes it a great choice for anyone who is approaching the NoSQL world.
2.9 (xiii Ratings)
Statistics
A First Course in Design and Analysis of Experiments
Suitable for either a service class for non-statistics graduate students or for statistics majors. Unlike nigh texts for the one-term grad/upper level course on experimental design, this book offers a superb residue of both analysis and design.
4.vi (1831 Ratings)
Statistics
An Introduction to Statistical Learning with Applications in R
This book presents some of the near important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, and much more than.
3.6 (21 Ratings)
Statistics
Artificial Intelligence: Foundations of Computational Agents
This is a textbook aimed at junior to senior undergraduate students and first-year graduate students. Information technology presents bogus intelligence (AI) using a coherent framework to written report the design of intelligent computational agents.
iii.8 (11 Ratings)
Statistics
Intro Stat with Randomization and Simulation
The foundations for inference are provided using randomization and simulation methods. Once a solid foundation is formed, a transition is made to traditional approaches, where the normal and t distributions are used for hypothesis testing and...
4.0 (34 Ratings)
Statistics
OpenIntro Statistics
Probability is optional, inference is primal, and nosotros feature real information whenever possible. Files for the entire book are freely available at openintro.org.
iv.4 (281 Ratings)
Statistics
The Elements of Statistical Learning: Data Mining, Inference, and Prediction
This book describes the important ideas in a multifariousness of fields such as medicine, biology, finance, and marketing in a common conceptual framework. While the arroyo is statistical, the accent is on concepts rather than mathematics.
3.nine (49 Ratings)
Statistics
Remember Bayes: Bayesian Statistics Fabricated Simple
Call up Bayes is an introduction to Bayesian statistics using computational methods. The premise of this book, and the other books in the Think X series, is that if you know how to program, you can employ that skill to learn other topics.
Languages: Python
3.6 (348 Ratings)
Statistics
Recall Stats: Exploratory Information Analysis in Python
This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python.
iv.3 (1646 Ratings)
Pattern Recognition and Machine Learning
This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents judge inference algorithms that permit fast approximate answers in situations where exact answers are non feasible.
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