Predictive Analytics

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  • Publisher : FT Press Analytics
  • Release : 30 October 2020
  • ISBN : 0136738516
  • Page : 350 pages
  • Rating : 4.5/5 from 103 voters

Predictive Analytics Book PDF summary

In Predictive Analytics: Data Mining, Machine Learning and Data Science for Practitioners, Dr. Dursun Delen illuminates state-of-the-art best practices for predictive analytics for students. Using predictive analytics techniques, students can uncover hidden patterns and correlations in their data, and leverage this insight to improve a wide range of business decisions. Delen's holistic approach covers all this, and more: Data mining processes, methods, and techniques The role and management of data Predictive analytics tools and metrics Techniques for text and web mining, and for sentiment analysis Integration with cutting-edge Big Data approaches Throughout, Delen promotes understanding by presenting numerous conceptual illustrations, motivational success stories, failed projects that teach important lessons, and simple, hands-on tutorials that set this guide apart from competitors.

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Predictive Analytics

Predictive Analytics
  • Author : Dursun Delen
  • Publisher : FT Press Analytics
  • Release Date : 2020-10-30
  • ISBN : 0136738516
DOWNLOAD BOOKPredictive Analytics

In Predictive Analytics: Data Mining, Machine Learning and Data Science for Practitioners, Dr. Dursun Delen illuminates state-of-the-art best practices for predictive analytics for students. Using predictive analytics techniques, students can uncover hidden patterns and correlations in their data, and leverage this insight to improve a wide range of business decisions. Delen's holistic approach covers all this, and more: Data mining processes, methods, and techniques The role and management of data Predictive analytics tools and metrics Techniques for text and web

Machine Learning Models and Algorithms for Big Data Classification

Machine Learning Models and Algorithms for Big Data Classification
  • Author : Shan Suthaharan
  • Publisher : Springer
  • Release Date : 2015-10-20
  • ISBN : 9781489976413
DOWNLOAD BOOKMachine Learning Models and Algorithms for Big Data Classification

This book presents machine learning models and algorithms to address big data classification problems. Existing machine learning techniques like the decision tree (a hierarchical approach), random forest (an ensemble hierarchical approach), and deep learning (a layered approach) are highly suitable for the system that can handle such problems. This book helps readers, especially students and newcomers to the field of big data and machine learning, to gain a quick understanding of the techniques and technologies; therefore, the theory, examples, and

Modern Management based on Big Data II and Machine Learning and Intelligent Systems III

Modern Management based on Big Data II and Machine Learning and Intelligent Systems III
  • Author : Anonim
  • Publisher : IOS Press
  • Release Date : 2021
  • ISBN : 9781643682259
DOWNLOAD BOOKModern Management based on Big Data II and Machine Learning and Intelligent Systems III

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow
  • Author : Aurélien Géron
  • Publisher : "O'Reilly Media, Inc."
  • Release Date : 2019-09-05
  • ISBN : 9781492032595
DOWNLOAD BOOKHands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow

Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems.

Data Science from Scratch

Data Science from Scratch
  • Author : Joel Grus
  • Publisher : "O'Reilly Media, Inc."
  • Release Date : 2015-04-14
  • ISBN : 9781491904404
DOWNLOAD BOOKData Science from Scratch

Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they’re also a good way to dive into the discipline without actually understanding data science. In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core

Big Data and Artificial Intelligence for Healthcare Applications

Big Data and Artificial Intelligence for Healthcare Applications
  • Author : Ankur Saxena,Nicolas Brault,Shazia Rashid
  • Publisher : CRC Press
  • Release Date : 2021-06-15
  • ISBN : 9781000387315
DOWNLOAD BOOKBig Data and Artificial Intelligence for Healthcare Applications

This book covers a wide range of topics on the role of Artificial Intelligence, Machine Learning, and Big Data for healthcare applications and deals with the ethical issues and concerns associated with it. This book explores the applications in different areas of healthcare and highlights the current research. "Big Data and Artificial Intelligence for Healthcare Applications" covers healthcare big data analytics, mobile health and personalized medicine, clinical trial data management and presents how Artificial Intelligence can be used for early

Machine Learning in Python

Machine Learning in Python
  • Author : Michael Bowles
  • Publisher : John Wiley & Sons
  • Release Date : 2015-03-30
  • ISBN : 9781118961742
DOWNLOAD BOOKMachine Learning in Python

This book shows readers how they can successfully analyze data using only two core machine learning algorithms---and how to do so using the popular Python programming language. These algorithms deal with common scenarios faced by all data analysts and data scientists. This book focuses on two algorithm families (linear methods and ensemble methods) that effectively predict outcomes. This type of problem covers a multitude of use cases (what ad to place on a web page, predicting prices in securities markets,

Machine Learning Algorithms

Machine Learning Algorithms
  • Author : Giuseppe Bonaccorso
  • Publisher : Packt Publishing Ltd
  • Release Date : 2017-07-24
  • ISBN : 9781785884511
DOWNLOAD BOOKMachine Learning Algorithms

Build strong foundation for entering the world of Machine Learning and data science with the help of this comprehensive guide About This Book Get started in the field of Machine Learning with the help of this solid, concept-rich, yet highly practical guide. Your one-stop solution for everything that matters in mastering the whats and whys of Machine Learning algorithms and their implementation. Get a solid foundation for your entry into Machine Learning by strengthening your roots (algorithms) with this comprehensive

Big Data, IoT, and Machine Learning

Big Data, IoT, and Machine Learning
  • Author : Rashmi Agrawal,Marcin Paprzycki,Neha Gupta
  • Publisher : CRC Press
  • Release Date : 2020-09-01
  • ISBN : 9781000098280
DOWNLOAD BOOKBig Data, IoT, and Machine Learning

The idea behind this book is to simplify the journey of aspiring readers and researchers to understand Big Data, IoT and Machine Learning. It also includes various real-time/offline applications and case studies in the fields of engineering, computer science, information security and cloud computing using modern tools. This book consists of two sections: Section I contains the topics related to Applications of Machine Learning, and Section II addresses issues about Big Data, the Cloud and the Internet of Things.

Intelligence Science and Big Data Engineering. Big Data and Machine Learning

Intelligence Science and Big Data Engineering. Big Data and Machine Learning
  • Author : Zhen Cui,Jinshan Pan,Shanshan Zhang,Liang Xiao,Jian Yang
  • Publisher : Springer Nature
  • Release Date : 2019-11-28
  • ISBN : 9783030362041
DOWNLOAD BOOKIntelligence Science and Big Data Engineering. Big Data and Machine Learning

The two volumes LNCS 11935 and 11936 constitute the proceedings of the 9th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2019, held in Nanjing, China, in October 2019. The 84 full papers presented were carefully reviewed and selected from 252 submissions.The papers are organized in two parts: visual data engineering; and big data and machine learning. They cover a large range of topics including information theoretic and Bayesian approaches, probabilistic graphical models, big data analysis, neural networks and neuro-informatics, bioinformatics, computational biology

Green Internet of Things and Machine Learning

Green Internet of Things and Machine Learning
  • Author : Roshani Raut,Sandeep Kautish,Zdzislaw Polkowski,Anil Kumar,Chuan-Ming Liu
  • Publisher : John Wiley & Sons
  • Release Date : 2022-01-10
  • ISBN : 9781119793120
DOWNLOAD BOOKGreen Internet of Things and Machine Learning

Health Economics and Financing Encapsulates different case studies where green-IOT and machine learning can be used for making significant progress towards improvising the quality of life and sustainable environment. The Internet of Things (IoT) is an evolving idea which is responsible for connecting billions of devices that acquire, perceive, and communicate data from their surroundings. Because this transmission of data uses significant energy, improving energy efficiency in IOT devices is a significant topic for research. The green internet of things (

Data Science on the Google Cloud Platform

Data Science on the Google Cloud Platform
  • Author : Valliappa Lakshmanan
  • Publisher : "O'Reilly Media, Inc."
  • Release Date : 2017-12-12
  • ISBN : 9781491974513
DOWNLOAD BOOKData Science on the Google Cloud Platform

Learn how easy it is to apply sophisticated statistical and machine learning methods to real-world problems when you build on top of the Google Cloud Platform (GCP). This hands-on guide shows developers entering the data science field how to implement an end-to-end data pipeline, using statistical and machine learning methods and tools on GCP. Through the course of the book, you’ll work through a sample business decision by employing a variety of data science approaches. Follow along by implementing

Machine Learning, Optimization, and Data Science

Machine Learning, Optimization, and Data Science
  • Author : Giuseppe Nicosia,Varun Ojha,Emanuele La Malfa,Giorgio Jansen,Vincenzo Sciacca,Panos Pardalos,Giovanni Giuffrida,Renato Umeton
  • Publisher : Springer Nature
  • Release Date : 2021-01-06
  • ISBN : 9783030645809
DOWNLOAD BOOKMachine Learning, Optimization, and Data Science

This two-volume set, LNCS 12565 and 12566, constitutes the refereed proceedings of the 6th International Conference on Machine Learning, Optimization, and Data Science, LOD 2020, held in Siena, Italy, in July 2020. The total of 116 full papers presented in this two-volume post-conference proceedings set was carefully reviewed and selected from 209 submissions. These research articles were written by leading scientists in the fields of machine learning, artificial intelligence, reinforcement learning, computational optimization, and data science presenting a substantial array of ideas, technologies, algorithms, methods, and

Practical Statistics for Data Scientists

Practical Statistics for Data Scientists
  • Author : Peter Bruce,Andrew Bruce
  • Publisher : "O'Reilly Media, Inc."
  • Release Date : 2017-05-10
  • ISBN : 9781491952917
DOWNLOAD BOOKPractical Statistics for Data Scientists

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 misuse, and gives you advice on what's important and what's not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’

The Immaculate Conception of Data

The Immaculate Conception of Data
  • Author : Kelly Bronson
  • Publisher : McGill-Queen's Press - MQUP
  • Release Date : 2022-09-15
  • ISBN : 9780228012542
DOWNLOAD BOOKThe Immaculate Conception of Data

Every new tractor now contains built-in sensors that collect data and stream it to cloud-based infrastructure. Seed and chemical companies are using these data, and these agribusinesses are a form of big tech alongside firms like Google and Facebook. The Immaculate Conception of Data peeks behind the secretive legal agreements surrounding agricultural big data to trace how it is used and with what consequences. Agribusinesses are among the oldest oligopoly corporations in the world, and their concentration gives them an