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Machine Learning with Go Quick Start Guide
Hands-on techniques for building supervised and unsupervised machine learning workflows
2019
EN
This quick start guide will bring the readers to a basic level of understanding when it comes to the Machine Learning (ML) development lifecycle, will introduce Go ML libraries and then will exemplify common ML methods such as Classification, Regression, and ClusteringKey FeaturesYour handy guide to building machine learning workflows in Go for real-world scenariosBuild predictive models using the popular supervised and unsupervised machine learning tec...
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Spark: The Definitive Guide
Big Data Processing Made Simple
2018
EN
Learn how to use, deploy, and maintain Apache Spark with this comprehensive guide, written by the creators of the open-source cluster-computing framework. With an emphasis on improvements and new features in Spark 2.0, authors Bill Chambers and Matei Zaharia break down Spark topics into distinct sections, each with unique goals.Youâ??ll explore the basic operations and common functions of Sparkâ??s structured APIs, as well as Structured Streaming, a new high-level API for building ...
Functional Programming for Java Developers
Tools for Better Concurrency, Abstraction, and Agility
2011
EN
Software development today is embracing functional programming (FP), whether it's for writing concurrent programs or for managing Big Data. Where does that leave Java developers? This concise book offers a pragmatic, approachable introduction to FP for Java developers or anyone who uses an object-oriented language.Dean Wampler, Java expert and author of Programming Scala (O'Reilly), shows you how to apply FP principles such as immutability, avoidance of side-effects, and h...
1996
EN
This classic book is the definitive real-world style guide for better Smalltalk programming. This author presents a set of patterns that organize all the informal experience successful Smalltalk programmers have learned the hard way. When programmers understand these patterns, they can write much more effective code. The concept of Smalltalk patterns is introduced, and the book explains why they work. Next, the book introduces proven patterns for working with methods, messages, state, coll...
2011
EN
API Design for C++ provides a comprehensive discussion of Application Programming Interface (API) development, from initial design through implementation, testing, documentation, release, versioning, maintenance, and deprecation. It is the only book that teaches the strategies of C++ API development, including interface design, versioning, scripting, and plug-in extensibility. Drawing from the author's experience on large scale, collaborative software projects, the text offers practical te...
Python: Real-World Data Science
Real-World Data Science
2016
EN
Unleash the power of Python and its robust data science capabilitiesKey FeaturesUnleash the power of Python 3 objectsLearn to use powerful Python libraries for effective data processing and analysisHarness the power of Python to analyze data and create insightful predictive modelsUnlock deeper insights into machine learning with this vital guide to cutting-edge predictive analyticsBook DescriptionThe Python: Real-Wor...
Practical MLOps
Operationalizing Machine Learning Models
2021
EN
Getting your models into production is the fundamental challenge of machine learning. MLOps offers a set of proven principles aimed at solving this problem in a reliable and automated way. This insightful guide takes you through what MLOps is (and how it differs from DevOps) and shows you how to put it into practice to operationalize your machine learning models.Current and aspiring machine learning engineers--or anyone familiar with data science and Python--will build a foundation...
Learning PySpark
Build data-intensive applications locally and deploy at scale using the combined powers of Python and Spark 2.0
2017
EN
Build data-intensive applications locally and deploy at scale using the combined powers of Python and Spark 2.0Key Features\[\*\] Learn why and how you can efficiently use Python to process data and build machine learning models in Apache Spark 2.0\[\*\] Develop and deploy efficient, scalable real-time Spark solutions\[\*\] Take your understanding of using Spark with Python to the next level with this jump start guideBook Descript...
2014
EN
A fast, easy-to-follow and clear tutorial to help you develop Parallel computing systems using Python. Along with explaining the fundamentals, the book will also introduce you to slightly advanced concepts and will help you in implementing these techniques in the real world. If you are an experienced Python programmer and are willing to utilize the available computing resources by parallelizing applications in a simple way, then this book is for you. You are required to have a basic knowle...
Big Data Architect???s Handbook
A guide to building proficiency in tools and systems used by leading big data experts
2018
EN
A comprehensive end-to-end guide that gives hands-on practice in big data and Artificial IntelligenceKey FeaturesLearn to build and run a big data application with sample codeExplore examples to implement activities that a big data architect performsUse Machine Learning and AI for structured and unstructured dataBook DescriptionThe big data architects are the “masters” of data, and hold high value in today’s market. Handling ...
Scala and Spark for Big Data Analytics
Explore the concepts of functional programming, data streaming, and machine learning
2017
EN
Harness the power of Scala to program Spark and analyze tonnes of data in the blink of an eye!Key Features\[\*\]Learn Scala’s sophisticated type system that combines Functional Programming and object-oriented concepts\[\*\]Work on a wide array of applications, from simple batch jobs to stream processing and machine learning\[\*\]Explore the most common as well as some complex use-cases to perform large-scale data analysis with Spark
Learning Python Design Patterns - Second Edition
Learning Python Design Patterns - Second Edition
2016
EN
Leverage the power of Python design patterns to solve real-world problems in software architecture and designKey Features\[\*\] Understand the structural, creational, and behavioral Python design patterns\[\*\] Get to know the context and application of design patterns to solve real-world problems in software architecture, design, and application development\[\*\] Get practical exposure through sample implementations in Python v3.5 for the desi...











