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Python Machine Learning Case Studies: Five Case Studies for the Data Scientist
Python Machine Learning Case Studies: Five Case Studies for the Data Scientist
Embrace machine learning approaches and Python to enable automatic rendering of rich insights and solve business problems. The book uses a hands-on case study-based approach to crack real-world applications to which machine learning concepts can be applied. These smarter machines will enable your business processes to achieve efficiencies on...
Practical Statistics for Data Scientists: 50 Essential Concepts
Practical Statistics for Data Scientists: 50 Essential Concepts

Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their...

Python Data Science Handbook: Essential Tools for Working with Data
Python Data Science Handbook: Essential Tools for Working with Data

For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib,...

Scalable Big Data Architecture: A practitioners guide to choosing relevant Big Data architecture
Scalable Big Data Architecture: A practitioners guide to choosing relevant Big Data architecture

This book highlights the different types of data architecture and illustrates the many possibilities hidden behind the term "Big Data", from the usage of No-SQL databases to the deployment of stream analytics architecture, machine learning, and governance.

Scalable Big Data Architecture covers real-world,...

Approximation Algorithms
Approximation Algorithms
Covering the basic techniques used in the latest research work, the author consolidates progress made so far, including some very recent and promising results, and conveys the beauty and excitement of work in the field. He gives clear, lucid explanations of key results and ideas, with intuitive proofs, and provides critical examples and numerous...
Introductory Statistics with R (Statistics and Computing)
Introductory Statistics with R (Statistics and Computing)
This book provides an elementary-level introduction to R, targeting both non-statistician scientists in various fields and students of statistics. The main mode of presentation is via code examples with liberal commenting of the code and the output, from the computational as well as the statistical viewpoint. Brief sections introduce the...
Python for Graph and Network Analysis (Advanced Information and Knowledge Processing)
Python for Graph and Network Analysis (Advanced Information and Knowledge Processing)

This research monograph provides the means to learn the theory and practice of graph and network analysis using the Python programming language. The social network analysis techniques, included, will help readers to efficiently analyze social data from Twitter, Facebook, LiveJournal, GitHub and many others at three levels of depth: ego,...

TensorFlow for Deep Learning: From Linear Regression to Reinforcement Learning
TensorFlow for Deep Learning: From Linear Regression to Reinforcement Learning

Learn how to solve challenging machine learning problems with TensorFlow, Google’s revolutionary new software library for deep learning. If you have some background in basic linear algebra and calculus, this practical book introduces machine-learning fundamentals by showing you how to design systems capable of detecting objects...

Computer Science: Notable Research and Discoveries (Frontiers of Science)
Computer Science: Notable Research and Discoveries (Frontiers of Science)
No one is certain how much more powerful and possibly intelligent computers will become in the 21st century. Exploring six prominent topics in computer science research, this title describes how computer scientists conduct research and attempt to formulate answers to important questions. Research published in journals, presented at conferences,...
Databases and Information Systems VI: Selected Papers from the Ninth International Baltic Conference, DB&IS 2010 - Volume 224 Frontiers in Artificial Intelligence and Applications
Databases and Information Systems VI: Selected Papers from the Ninth International Baltic Conference, DB&IS 2010 - Volume 224 Frontiers in Artificial Intelligence and Applications
This volume presents papers from the Ninth International Baltic Conference on Databases and Information Systems (Baltic DB&IS 2010) which took place in Riga, Latvia, in July 2010. Since this successful biennial series began in 1994, the Baltic DB&IS conferences have become an international forum of high scientific criteria for...
From Semantics to Computer Science: Essays in Honour of Gilles Kahn
From Semantics to Computer Science: Essays in Honour of Gilles Kahn
Gilles Kahn was one of the most influential figures in the development of computer science and information technology, not only in Europe but throughout the world. This volume of articles by several leading computer scientists serves as a fitting memorial to Kahn's achievements and reflects the broad range of subjects to which he contributed...
Big Data SMACK: A Guide to Apache Spark, Mesos, Akka, Cassandra, and Kafka
Big Data SMACK: A Guide to Apache Spark, Mesos, Akka, Cassandra, and Kafka

Learn how to integrate full-stack open source big data architecture and to choose the correct technology―Scala/Spark, Mesos, Akka, Cassandra, and Kafka―in every layer. 

Big data architecture is becoming a requirement for many different enterprises. So far, however, the focus has largely been on collecting,...

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