• Home
  • Practical Machine Learning for Data Analysis Using Python

Practical Machine Learning for Data Analysis Using Python

Practical Machine Learning for Data Analysis Using Python
  • Author : Abdulhamit Subasi
  • Publsiher : Academic Press
  • Release : 05 June 2020
  • ISBN : 0128213809
  • Pages : 534 pages
  • Rating : 4/5 from 21 ratings
GET THIS BOOKPractical Machine Learning for Data Analysis Using Python

Summary:
Practical Machine Learning for Data Analysis Using Python is a problem solver’s guide for creating real-world intelligent systems. It provides a comprehensive approach with concepts, practices, hands-on examples, and sample code. The book teaches readers the vital skills required to understand and solve different problems with machine learning. It teaches machine learning techniques necessary to become a successful practitioner, through the presentation of real-world case studies in Python machine learning ecosystems. The book also focuses on building a foundation of machine learning knowledge to solve different real-world case studies across various fields, including biomedical signal analysis, healthcare, security, economics, and finance. Moreover, it covers a wide range of machine learning models, including regression, classification, and forecasting. The goal of the book is to help a broad range of readers, including IT professionals, analysts, developers, data scientists, engineers, and graduate students, to solve their own real-world problems. Offers a comprehensive overview of the application of machine learning tools in data analysis across a wide range of subject areas Teaches readers how to apply machine learning techniques to biomedical signals, financial data, and healthcare data Explores important classification and regression algorithms as well as other machine learning techniques Explains how to use Python to handle data extraction, manipulation, and exploration techniques, as well as how to visualize data spread across multiple dimensions and extract useful features


Practical Machine Learning for Data Analysis Using Python

Practical Machine Learning for Data Analysis Using Python
  • Author : Abdulhamit Subasi
  • Publisher : Academic Press
  • Release : 05 June 2020
GET THIS BOOKPractical Machine Learning for Data Analysis Using Python

Practical Machine Learning for Data Analysis Using Python is a problem solver’s guide for creating real-world intelligent systems. It provides a comprehensive approach with concepts, practices, hands-on examples, and sample code. The book teaches readers the vital skills required to understand and solve different problems with machine learning. It teaches machine learning techniques necessary to become a successful practitioner, through the presentation of real-world case studies in Python machine learning ecosystems. The book also focuses on building a foundation


Practical Machine Learning with Python

Practical Machine Learning with Python
  • Author : Dipanjan Sarkar,Raghav Bali,Tushar Sharma
  • Publisher : Apress
  • Release : 20 December 2017
GET THIS BOOKPractical Machine Learning with Python

Master the essential skills needed to recognize and solve complex problems with machine learning and deep learning. Using real-world examples that leverage the popular Python machine learning ecosystem, this book is your perfect companion for learning the art and science of machine learning to become a successful practitioner. The concepts, techniques, tools, frameworks, and methodologies used in this book will teach you how to think, design, build, and execute machine learning systems and projects successfully. Practical Machine Learning with Python


Practical Machine Learning

Practical Machine Learning
  • Author : Sunila Gollapudi
  • Publisher : Packt Publishing Ltd
  • Release : 30 January 2016
GET THIS BOOKPractical Machine Learning

Tackle the real-world complexities of modern machine learning with innovative, cutting-edge, techniques About This Book Fully-coded working examples using a wide range of machine learning libraries and tools, including Python, R, Julia, and Spark Comprehensive practical solutions taking you into the future of machine learning Go a step further and integrate your machine learning projects with Hadoop Who This Book Is For This book has been created for data scientists who want to see machine learning in action and explore


Practical Machine Learning with H2O

Practical Machine Learning with H2O
  • Author : Darren Cook
  • Publisher : "O'Reilly Media, Inc."
  • Release : 05 December 2016
GET THIS BOOKPractical Machine Learning with H2O

Machine learning has finally come of age. With H2O software, you can perform machine learning and data analysis using a simple open source framework that’s easy to use, has a wide range of OS and language support, and scales for big data. This hands-on guide teaches you how to use H20 with only minimal math and theory behind the learning algorithms. If you’re familiar with R or Python, know a bit of statistics, and have some experience


Practical Machine Learning and Image Processing

Practical Machine Learning and Image Processing
  • Author : Himanshu Singh
  • Publisher : Apress
  • Release : 26 February 2019
GET THIS BOOKPractical Machine Learning and Image Processing

Gain insights into image-processing methodologies and algorithms, using machine learning and neural networks in Python. This book begins with the environment setup, understanding basic image-processing terminology, and exploring Python concepts that will be useful for implementing the algorithms discussed in the book. You will then cover all the core image processing algorithms in detail before moving onto the biggest computer vision library: OpenCV. You’ll see the OpenCV algorithms and how to use them for image processing. The next section


Deep Learning for Coders with fastai and PyTorch

Deep Learning for Coders with fastai and PyTorch
  • Author : Jeremy Howard,Sylvain Gugger
  • Publisher : "O'Reilly Media, Inc."
  • Release : 29 June 2020
GET THIS BOOKDeep Learning for Coders with fastai and PyTorch

Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model


Practical Machine Learning with R

Practical Machine Learning with R
  • Author : Brindha Priyadarshini Jeyaraman,Ludvig Renbo Olsen,Monicah Wambugu
  • Publisher : Packt Publishing Ltd
  • Release : 30 August 2019
GET THIS BOOKPractical Machine Learning with R

Understand how machine learning works and get hands-on experience of using R to build algorithms that can solve various real-world problems Key Features Gain a comprehensive overview of different machine learning techniques Explore various methods for selecting a particular algorithm Implement a machine learning project from problem definition through to the final model Book Description With huge amounts of data being generated every moment, businesses need applications that apply complex mathematical calculations to data repeatedly and at speed. With machine


Python Machine Learning

Python Machine Learning
  • Author : Sebastian Raschka
  • Publisher : Packt Publishing Ltd
  • Release : 23 September 2015
GET THIS BOOKPython Machine Learning

Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics About This Book Leverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualization Learn effective strategies and best practices to improve and optimize machine learning systems and algorithms Ask – and answer – tough questions of your data with robust statistical models, built for a range of datasets Who This Book Is For If you want to find out how to use Python to


Mastering Machine Learning with Python in Six Steps

Mastering Machine Learning with Python in Six Steps
  • Author : Manohar Swamynathan
  • Publisher : Apress
  • Release : 02 October 2019
GET THIS BOOKMastering Machine Learning with Python in Six Steps

Explore fundamental to advanced Python 3 topics in six steps, all designed to make you a worthy practitioner. This updated version’s approach is based on the “six degrees of separation” theory, which states that everyone and everything is a maximum of six steps away and presents each topic in two parts: theoretical concepts and practical implementation using suitable Python 3 packages. You’ll start with the fundamentals of Python 3 programming language, machine learning history, evolution, and the system development frameworks. Key


Introduction to Machine Learning with Python

Introduction to Machine Learning with Python
  • Author : Andreas C. Müller,Sarah Guido
  • Publisher : "O'Reilly Media, Inc."
  • Release : 26 September 2016
GET THIS BOOKIntroduction to Machine Learning with Python

Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination. You’ll learn the steps necessary to create a successful machine-learning application with Python and the


Practical Machine Learning in R

Practical Machine Learning in R
  • Author : Fred Nwanganga,Mike Chapple
  • Publisher : John Wiley & Sons
  • Release : 10 June 2020
GET THIS BOOKPractical Machine Learning in R

Guides professionals and students through the rapidly growing field of machine learning with hands-on examples in the popular R programming language Machine learning—a branch of Artificial Intelligence (AI) which enables computers to improve their results and learn new approaches without explicit instructions—allows organizations to reveal patterns in their data and incorporate predictive analytics into their decision-making process. Practical Machine Learning in R provides a hands-on approach to solving business problems with intelligent, self-learning computer algorithms. Bestselling author and


Advanced Data Analytics Using Python

Advanced Data Analytics Using Python
  • Author : Sayan Mukhopadhyay
  • Publisher : Apress
  • Release : 29 March 2018
GET THIS BOOKAdvanced Data Analytics Using Python

Gain a broad foundation of advanced data analytics concepts and discover the recent revolution in databases such as Neo4j, Elasticsearch, and MongoDB. This book discusses how to implement ETL techniques including topical crawling, which is applied in domains such as high-frequency algorithmic trading and goal-oriented dialog systems. You’ll also see examples of machine learning concepts such as semi-supervised learning, deep learning, and NLP. Advanced Data Analytics Using Python also covers important traditional data analysis techniques such as time


Practical Machine Learning for Streaming Data with Python

Practical Machine Learning for Streaming Data with Python
  • Author : Sayan Putatunda
  • Publisher : Apress
  • Release : 28 June 2021
GET THIS BOOKPractical Machine Learning for Streaming Data with Python

Design, develop, and validate machine learning models with streaming data using the Scikit-Multiflow framework. This book is a quick start guide for data scientists and machine learning engineers looking to implement machine learning models for streaming data with Python to generate real-time insights. You'll start with an introduction to streaming data, the various challenges associated with it, some of its real-world business applications, and various windowing techniques. You'll then examine incremental and online learning algorithms, and the concept of model


Data Mining: Practical Machine Learning Tools and Techniques

Data Mining: Practical Machine Learning Tools and Techniques
  • Author : Ian H. Witten,Eibe Frank,Mark A. Hall
  • Publisher : Elsevier
  • Release : 03 February 2011
GET THIS BOOKData Mining: Practical Machine Learning Tools and Techniques

Data Mining: Practical Machine Learning Tools and Techniques, Third Edition, offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining. Thorough updates reflect


Deep Learning with Python

Deep Learning with Python
  • Author : Francois Chollet
  • Publisher : Manning Publications
  • Release : 28 October 2017
GET THIS BOOKDeep Learning with Python

Summary Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher Fran�ois Chollet, this book builds your understanding through intuitive explanations and practical examples. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Machine learning has made remarkable progress in recent years. We went from near-unusable speech and image recognition,