Showing results for "patrick r nicolas"
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Scala:Applied Machine Learning
Master the art of Machine Learning in Scala
2017
EN
Leverage the power of Scala and master the art of building, improving, and validating scalable machine learning and AI applications using Scala's most advanced and finest features.Key Features\[\*\] Build functional, type-safe routines to interact with relational and NoSQL databases with the help of the tutorials and examples provided\[\*\] Leverage your expertise in Scala programming to create and customize your own scalable machine learning algorithms...
2017
EN
Scala will be a valuable tool to have on hand during your data science journey for everything from data cleaning to cutting-edge machine learningAbout This BookBuild data science and data engineering solutions with easeAn in-depth look at each stage of the data analysis process — from reading and collecting data to distributed analyticsExplore a broad variety of data processing, machine learning, and genetic algorithms through di...
2014
EN
Are you curious about AI? All you need is a good understanding of the Scala programming language, a basic knowledge of statistics, a keen interest in Big Data processing, and this book!
Scala for Machine Learning
Build systems for data processing, machine learning, and deep learning
2017
EN
Leverage Scala and Machine Learning to study and construct systems that can learn from dataKey Features\[\*\]Explore a broad variety of data processing, machine learning, and genetic algorithms through diagrams, mathematical formulation, and updated source code in Scala\[\*\]Take your expertise in Scala programming to the next level by creating and customizing AI applications\[\*\]Experiment with different techniques and evaluate their benefits...
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2011
EN
The leading introduction to computer algorithms in use today, including fifty algorithms every programmer should knowPrinceton Computer Science professors, Robert Sedgewick and Kevin Wayne, survey the most important computer algorithms in use and of interest to anyone working in science, mathematics, and engineering, and those who use computation in the liberal arts. They provide a full treatment of data structures and algorithms for key areas that enable you to co...
Programming Collective Intelligence
Building Smart Web 2.0 Applications
2008
EN
Want to tap the power behind search rankings, product recommendations, social bookmarking, and online matchmaking? This fascinating book demonstrates how you can build Web 2.0 applications to mine the enormous amount of data created by people on the Internet. With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found ...
Python Machine Learning
Learn how to build powerful Python machine learning algorithms to generate useful data insights with this data analysis tutorial
2015
EN
Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analyticsKey FeaturesLeverage Python’s most powerful open-source libraries for deep learning, data wrangling, and data visualizationLearn effective strategies and best practices to improve and optimize machine learning systems and algorithmsAsk – and answer – tough questions of your data with robust statistical models, built for a range of datasets...
The Art of R Programming
A Tour of Statistical Software Design
2011
EN
R is the world's most popular language for developing statistical software: Archaeologists use it to track the spread of ancient civilizations, drug companies use it to discover which medications are safe and effective, and actuaries use it to assess financial risks and keep economies running smoothly.The Art of R Programming takes you on a guided tour of software development with R, from basic types and data structures to advanced topics like closures, recursion, and anon...
Joe Celko's SQL for Smarties
Advanced SQL Programming
2010
EN
Joe Celkos SQL for Smarties: Advanced SQL Programming offers tips and techniques in advanced programming. This book is the fourth edition and it consists of 39 chapters, starting with a comparison between databases and file systems. It covers transactions and currency control, schema level objects, locating data and schema numbers, base tables, and auxiliary tables. Furthermore, procedural, semi-procedural, and declarative programming are explored in this book. The book also presents the d...
R in a Nutshell
A Desktop Quick Reference
2012
EN
If you’re considering R for statistical computing and data visualization, this book provides a quick and practical guide to just about everything you can do with the open source R language and software environment. You’ll learn how to write R functions and use R packages to help you prepare, visualize, and analyze data. Author Joseph Adler illustrates each process with a wealth of examples from medicine, business, and sports.Updated for R 2.14 and 2.15, this second edition includes...
2016
EN
Haskell is a purely functional language that allows programmers to rapidly develop clear, concise, and correct software. The language has grown in popularity in recent years, both in teaching and in industry. This book is based on the author's experience of teaching Haskell for more than twenty years. All concepts are explained from first principles and no programming experience is required, making this book accessible to a broad spectrum of readers. While Part I focuses on basic concepts,...
Algorithms
Part I
2014
EN
This book is Part I of the fourth edition of Robert Sedgewick and Kevin Wayne’s Algorithms, the leading textbook on algorithms today, widely used in colleges and universities worldwide. Part I contains Chapters 1 through 3 of the book. The fourth edition of Algorithms surveys the most important computer algorithms currently in use and provides a full treatment of data structures and algorithms for sorting, searching, graph processing, and...











