Mastering Machine Learning With R Third Edition

Mastering Machine Learning with R   Third Edition PDF
Author: Cory Lesmeister
Publisher:
ISBN:
Size: 75.29 MB
Format: PDF
Category :
Languages : en
Pages : 354
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Mastering Machine Learning With R Third Edition

by Cory Lesmeister, Mastering Machine Learning With R Third Edition Books available in PDF, EPUB, Mobi Format. Download Mastering Machine Learning With R Third Edition books, Stay updated with expert techniques for solving data analytics and machine learning challenges and gain insights from complex projects and power up your applications Key Features Build independent machine learning (ML) systems leveraging the best features of R 3.5 Understand and apply different machine learning techniques using real-world examples Use methods such as multi-class classification, regression, and clustering Book Description Given the growing popularity of the R-zerocost statistical programming environment, there has never been a better time to start applying ML to your data. This book will teach you advanced techniques in ML, using? the latest code in R 3.5. You will delve into various complex features of supervised learning, unsupervised learning, and reinforcement learning algorithms to design efficient and powerful ML models. This newly updated edition is packed with fresh examples covering a range of tasks from different domains. Mastering Machine Learning with R starts by showing you how to quickly manipulate data and prepare it for analysis. You will explore simple and complex models and understand how to compare them. You'll also learn to use the latest library support, such as TensorFlow and Keras-R, for performing advanced computations. Additionally, you'll explore complex topics, such as natural language processing (NLP), time series analysis, and clustering, which will further refine your skills in developing applications. Each chapter will help you implement advanced ML algorithms using real-world examples. You'll even be introduced to reinforcement learning, along with its various use cases and models. In the concluding chapters, you'll get a glimpse into how some of these blackbox models can be diagnosed and understood. By the end of this book, you'll be equipped with the skills to deploy ML techniques in your own projects or at work. What you will learn Prepare data for machine learning methods with ease Understand how to write production-ready code and package it for use Produce simple and effective data visualizations for improved insights Master advanced methods, such as Boosted Trees and deep neural networks Use natural language processing to extract insights in relation to text Implement tree-based classifiers, including Random Forest and Boosted Tree Who this book is for This book is for data science professionals, machine learning engineers, or anyone who is looking for the ideal guide to help them implement ...


Mastering Machine Learning With R

Mastering Machine Learning with R PDF
Author: Cory Lesmeister
Publisher: Packt Publishing Ltd
ISBN: 1789613566
Size: 51.78 MB
Format: PDF, Mobi
Category : Computers
Languages : en
Pages : 354
View: 6869

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Mastering Machine Learning With R

by Cory Lesmeister, Mastering Machine Learning With R Books available in PDF, EPUB, Mobi Format. Download Mastering Machine Learning With R books, Stay updated with expert techniques for solving data analytics and machine learning challenges and gain insights from complex projects and power up your applications Key Features Build independent machine learning (ML) systems leveraging the best features of R 3.5 Understand and apply different machine learning techniques using real-world examples Use methods such as multi-class classification, regression, and clustering Book Description Given the growing popularity of the R-zerocost statistical programming environment, there has never been a better time to start applying ML to your data. This book will teach you advanced techniques in ML ,using? the latest code in R 3.5. You will delve into various complex features of supervised learning, unsupervised learning, and reinforcement learning algorithms to design efficient and powerful ML models. This newly updated edition is packed with fresh examples covering a range of tasks from different domains. Mastering Machine Learning with R starts by showing you how to quickly manipulate data and prepare it for analysis. You will explore simple and complex models and understand how to compare them. You’ll also learn to use the latest library support, such as TensorFlow and Keras-R, for performing advanced computations. Additionally, you’ll explore complex topics, such as natural language processing (NLP), time series analysis, and clustering, which will further refine your skills in developing applications. Each chapter will help you implement advanced ML algorithms using real-world examples. You’ll even be introduced to reinforcement learning, along with its various use cases and models. In the concluding chapters, you’ll get a glimpse into how some of these blackbox models can be diagnosed and understood. By the end of this book, you’ll be equipped with the skills to deploy ML techniques in your own projects or at work. What you will learn Prepare data for machine learning methods with ease Understand how to write production-ready code and package it for use Produce simple and effective data visualizations for improved insights Master advanced methods, such as Boosted Trees and deep neural networks Use natural language processing to extract insights in relation to text Implement tree-based classifiers, including Random Forest and Boosted Tree Who this book is for This book is for data science professionals, machine learning engineers, or anyone who is looking for the ideal guide to help them implement advanced machine learning algorithms. The book will help you take your skills to the next level and advance further in this field. Working knowledge of machine learning with R is mandatory.


Mastering Machine Learning With Python In Six Steps

Mastering Machine Learning with Python in Six Steps PDF
Author: Manohar Swamynathan
Publisher: Apress
ISBN: 1484228669
Size: 49.27 MB
Format: PDF, Mobi
Category : Computers
Languages : en
Pages : 358
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Mastering Machine Learning With Python In Six Steps

by Manohar Swamynathan, Mastering Machine Learning With Python In Six Steps Books available in PDF, EPUB, Mobi Format. Download Mastering Machine Learning With Python In Six Steps books, Master machine learning with Python in six steps and explore fundamental to advanced topics, all designed to make you a worthy practitioner. This book’s approach is based on the “Six degrees of separation” theory, which states that everyone and everything is a maximum of six steps away. Mastering Machine Learning with Python in Six Steps presents each topic in two parts: theoretical concepts and practical implementation using suitable Python packages. You’ll learn the fundamentals of Python programming language, machine learning history, evolution, and the system development frameworks. Key data mining/analysis concepts, such as feature dimension reduction, regression, time series forecasting and their efficient implementation in Scikit-learn are also covered. Finally, you’ll explore advanced text mining techniques, neural networks and deep learning techniques, and their implementation. All the code presented in the book will be available in the form of iPython notebooks to enable you to try out these examples and extend them to your advantage. What You'll Learn Examine the fundamentals of Python programming language Review machine Learning history and evolution Understand machine learning system development frameworks Implement supervised/unsupervised/reinforcement learning techniques with examples Explore fundamental to advanced text mining techniques Implement various deep learning frameworks Who This Book Is For Python developers or data engineers looking to expand their knowledge or career into machine learning area. Non-Python (R, SAS, SPSS, Matlab or any other language) machine learning practitioners looking to expand their implementation skills in Python. Novice machine learning practitioners looking to learn advanced topics, such as hyperparameter tuning, various ensemble techniques, natural language processing (NLP), deep learning, and basics of reinforcement learning.


Advanced Machine Learning With R

Advanced Machine Learning with R PDF
Author: Cory Lesmeister
Publisher:
ISBN: 9781838641771
Size: 61.84 MB
Format: PDF
Category : Computers
Languages : en
Pages : 664
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Advanced Machine Learning With R

by Cory Lesmeister, Advanced Machine Learning With R Books available in PDF, EPUB, Mobi Format. Download Advanced Machine Learning With R books, Master machine learning techniques with real-world projects that interface TensorFlow with R, H2O, MXNet, and other languages Key Features Gain expertise in machine learning, deep learning and other techniques Build intelligent end-to-end projects for finance, social media, and a variety of domains Implement multi-class classification, regression, and clustering Book Description R is one of the most popular languages when it comes to exploring the mathematical side of machine learning and easily performing computational statistics. This Learning Path shows you how to leverage the R ecosystem to build efficient machine learning applications that carry out intelligent tasks within your organization. You'll tackle realistic projects such as building powerful machine learning models with ensembles to predict employee attrition. You'll explore different clustering techniques to segment customers using wholesale data and use TensorFlow and Keras-R for performing advanced computations. You'll also be introduced to reinforcement learning along with its various use cases and models. Additionally, it shows you how some of these black-box models can be diagnosed and understood. By the end of this Learning Path, you'll be equipped with the skills you need to deploy machine learning techniques in your own projects. This Learning Path includes content from the following Packt products: R Machine Learning Projects by Dr. Sunil Kumar Chinnamgari Mastering Machine Learning with R - Third Edition by Cory Lesmeister What you will learn Develop a joke recommendation engine to recommend jokes that match users' tastes Build autoencoders for credit card fraud detection Work with image recognition and convolutional neural networks Make predictions for casino slot machine using reinforcement learning Implement NLP techniques for sentiment analysis and customer segmentation Produce simple and effective data visualizations for improved insights Use NLP to extract insights for text Implement tree-based classifiers including random forest and boosted tree Who this book is for If you are a data analyst, data scientist, or machine learning developer this is an ideal Learning Path for you. Each project will help you test your skills in implementing machine learning algorithms and techniques. A basic understanding of machine learning and working knowledge of R programming is necessary to get the most out of this Learning Path.


R Unleash Machine Learning Techniques

R  Unleash Machine Learning Techniques PDF
Author: Raghav Bali
Publisher: Packt Publishing Ltd
ISBN: 1787128288
Size: 49.94 MB
Format: PDF, Docs
Category : Computers
Languages : en
Pages : 1123
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R Unleash Machine Learning Techniques

by Raghav Bali, R Unleash Machine Learning Techniques Books available in PDF, EPUB, Mobi Format. Download R Unleash Machine Learning Techniques books, Find out how to build smarter machine learning systems with R. Follow this three module course to become a more fluent machine learning practitioner. About This Book Build your confidence with R and find out how to solve a huge range of data-related problems Get to grips with some of the most important machine learning techniques being used by data scientists and analysts across industries today Don't just learn – apply your knowledge by following featured practical projects covering everything from financial modeling to social media analysis Who This Book Is For Aimed for intermediate-to-advanced people (especially data scientist) who are already into the field of data science What You Will Learn Get to grips with R techniques to clean and prepare your data for analysis, and visualize your results Implement R machine learning algorithms from scratch and be amazed to see the algorithms in action Solve interesting real-world problems using machine learning and R as the journey unfolds Write reusable code and build complete machine learning systems from the ground up Learn specialized machine learning techniques for text mining, social network data, big data, and more Discover the different types of machine learning models and learn which is best to meet your data needs and solve your analysis problems Evaluate and improve the performance of machine learning models Learn specialized machine learning techniques for text mining, social network data, big data, and more In Detail R is the established language of data analysts and statisticians around the world. And you shouldn't be afraid to use it... This Learning Path will take you through the fundamentals of R and demonstrate how to use the language to solve a diverse range of challenges through machine learning. Accessible yet comprehensive, it provides you with everything you need to become more a more fluent data professional, and more confident with R. In the first module you'll get to grips with the fundamentals of R. This means you'll be taking a look at some of the details of how the language works, before seeing how to put your knowledge into practice to build some simple machine learning projects that could prove useful for a range of real world problems. For the following two modules we'll begin to investigate machine learning algorithms in more detail. To build upon the basics, you'll get to work on three different projects that will test your skills. Covering some of the most important algorithms and featuring some of the most popular R packages, they're all focused on solving real problems in different areas, ranging from finance to social media. This Learning Path has been curated from three Packt products: R Machine Learning By Example By Raghav Bali, Dipanjan Sarkar Machine Learning with R Learning - Second Edition By Brett Lantz Mastering Machine Learning with R By Cory Lesmeister Style and approach This is an enticing learning path that starts from the very basics to gradually pick up pace as the story unfolds. Each concept is first defined in the larger context of things succinctly, followed by a detailed explanation of their application. Each topic is explained with the help of a project that solves a real-world problem involving hands-on work thus giving you a deep insight into the world of machine learning.


Mastering Machine Learning With Scikit Learn

Mastering Machine Learning with scikit learn PDF
Author: Gavin Hackeling
Publisher: Packt Publishing Ltd
ISBN: 1788298497
Size: 66.52 MB
Format: PDF, ePub
Category : Computers
Languages : en
Pages : 254
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Mastering Machine Learning With Scikit Learn

by Gavin Hackeling, Mastering Machine Learning With Scikit Learn Books available in PDF, EPUB, Mobi Format. Download Mastering Machine Learning With Scikit Learn books, Use scikit-learn to apply machine learning to real-world problems About This Book Master popular machine learning models including k-nearest neighbors, random forests, logistic regression, k-means, naive Bayes, and artificial neural networks Learn how to build and evaluate performance of efficient models using scikit-learn Practical guide to master your basics and learn from real life applications of machine learning Who This Book Is For This book is intended for software engineers who want to understand how common machine learning algorithms work and develop an intuition for how to use them, and for data scientists who want to learn about the scikit-learn API. Familiarity with machine learning fundamentals and Python are helpful, but not required. What You Will Learn Review fundamental concepts such as bias and variance Extract features from categorical variables, text, and images Predict the values of continuous variables using linear regression and K Nearest Neighbors Classify documents and images using logistic regression and support vector machines Create ensembles of estimators using bagging and boosting techniques Discover hidden structures in data using K-Means clustering Evaluate the performance of machine learning systems in common tasks In Detail Machine learning is the buzzword bringing computer science and statistics together to build smart and efficient models. Using powerful algorithms and techniques offered by machine learning you can automate any analytical model. This book examines a variety of machine learning models including popular machine learning algorithms such as k-nearest neighbors, logistic regression, naive Bayes, k-means, decision trees, and artificial neural networks. It discusses data preprocessing, hyperparameter optimization, and ensemble methods. You will build systems that classify documents, recognize images, detect ads, and more. You will learn to use scikit-learn's API to extract features from categorical variables, text and images; evaluate model performance, and develop an intuition for how to improve your model's performance. By the end of this book, you will master all required concepts of scikit-learn to build efficient models at work to carry out advanced tasks with the practical approach. Style and approach This book is motivated by the belief that you do not understand something until you can describe it simply. Work through toy problems to develop your understanding of the learning algorithms and models, then apply your learnings to real-life problems.


Mastering Scientific Computing With R

Mastering Scientific Computing with R PDF
Author: Paul Gerrard
Publisher: Packt Publishing Ltd
ISBN: 1783555262
Size: 35.14 MB
Format: PDF, ePub, Docs
Category : Computers
Languages : en
Pages : 432
View: 575

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Mastering Scientific Computing With R

by Paul Gerrard, Mastering Scientific Computing With R Books available in PDF, EPUB, Mobi Format. Download Mastering Scientific Computing With R books, If you want to learn how to quantitatively answer scientific questions for practical purposes using the powerful R language and the open source R tool ecosystem, this book is ideal for you. It is ideally suited for scientists who understand scientific concepts, know a little R, and want to be able to start applying R to be able to answer empirical scientific questions. Some R exposure is helpful, but not compulsory.


Mastering R Programming

Mastering R Programming PDF
Author: Selva Prabhakaran
Publisher:
ISBN:
Size: 25.68 MB
Format: PDF, Docs
Category :
Languages : en
Pages :
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Mastering R Programming

by Selva Prabhakaran, Mastering R Programming Books available in PDF, EPUB, Mobi Format. Download Mastering R Programming books, "R is a statistical programming language that allows you to build probabilistic models, perform data science, and build machine learning algorithms. R has a great package ecosystem that enables developers to conduct data visualization to data analysis.This video covers advanced-level concepts in R programming and demonstrates industry best practices. This is an advanced R course with an intensive focus on machine learning concepts in depth and applying them in the real world with R. We start off with pre-model-building activities such as univariate and bivariate analysis, outlier detection, and missing value treatment featuring the mice package. We then take a look linear and non-linear regression modeling and classification models, and check out the math behind the working of classification algorithms. We then shift our focus to unsupervised learning algorithms, time series analysis and forecasting models, and text analytics. We will see how to create a Term Document Matrix, normalize with TF-IDF, and draw a word cloud. We'll also check out how cosine similarity can be used to score similar documents and how Latent Semantic Indexing (LSI) can be used as a vector space model to group similar documents. Later, the course delves into constructing charts using the Ggplot2 package and multiple strategies to speed up R code. We then go over the powerful `dplyr` and `data.table` packages and familiarize ourselves to work with the pipe operator during the process. We will learn to write and interface C++ code in R using the powerful Rcpp package. We'll complete our journey with building an R package using facilities from the roxygen2 and dev tools packages. By the end of the course, you will have a solid knowledge of machine learning and the R language itself. You'll also solve numerous coding challenges throughout the course."--Resource description page.


Mastering Data Analysis With R

Mastering Data Analysis with R PDF
Author: Gergely Daroczi
Publisher: Packt Publishing Ltd
ISBN: 1783982039
Size: 76.67 MB
Format: PDF, Kindle
Category : Computers
Languages : en
Pages : 396
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Mastering Data Analysis With R

by Gergely Daroczi, Mastering Data Analysis With R Books available in PDF, EPUB, Mobi Format. Download Mastering Data Analysis With R books, Gain sharp insights into your data and solve real-world data science problems with R—from data munging to modeling and visualization About This Book Handle your data with precision and care for optimal business intelligence Restructure and transform your data to inform decision-making Packed with practical advice and tips to help you get to grips with data mining Who This Book Is For If you are a data scientist or R developer who wants to explore and optimize your use of R's advanced features and tools, this is the book for you. A basic knowledge of R is required, along with an understanding of database logic. What You Will Learn Connect to and load data from R's range of powerful databases Successfully fetch and parse structured and unstructured data Transform and restructure your data with efficient R packages Define and build complex statistical models with glm Develop and train machine learning algorithms Visualize social networks and graph data Deploy supervised and unsupervised classification algorithms Discover how to visualize spatial data with R In Detail R is an essential language for sharp and successful data analysis. Its numerous features and ease of use make it a powerful way of mining, managing, and interpreting large sets of data. In a world where understanding big data has become key, by mastering R you will be able to deal with your data effectively and efficiently. This book will give you the guidance you need to build and develop your knowledge and expertise. Bridging the gap between theory and practice, this book will help you to understand and use data for a competitive advantage. Beginning with taking you through essential data mining and management tasks such as munging, fetching, cleaning, and restructuring, the book then explores different model designs and the core components of effective analysis. You will then discover how to optimize your use of machine learning algorithms for classification and recommendation systems beside the traditional and more recent statistical methods. Style and approach Covering the essential tasks and skills within data science, Mastering Data Analysis provides you with solutions to the challenges of data science. Each section gives you a theoretical overview before demonstrating how to put the theory to work with real-world use cases and hands-on examples.


Python Machine Learning

Python Machine Learning PDF
Author: John Code
Publisher: Independently Published
ISBN:
Size: 19.91 MB
Format: PDF, ePub, Mobi
Category :
Languages : en
Pages : 157
View: 5014

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Python Machine Learning

by John Code, Python Machine Learning Books available in PDF, EPUB, Mobi Format. Download Python Machine Learning books, Are you new to machine learning and looking to eventually launch a career in Python? Do you want to learn how to do machine learning with Python but you have problems getting started? Machine learning is a subject that has quickly become popular in a wide range of domains such as Data Science, Artificial intelligence among others. The use of machine learning in these domains offers incredible opportunities. If you are just starting your career, this could just be the best decision you make. Have you been thinking of learning Python as your first programming language? Do you have data that you have generated and do not know where to start analyzing them? Are you interested in digesting your big data into meaningful information that will inform decision makers? Well, you have come to the right place! So many people think that they need to have expertise in math and programming for them to use Python at all. Trust me, you need zero-experience! All you need is interest and a strong motivation to learn all these things. You may be thinking to yourself "But why Python?" Well, there are so many reasons why Python is the best programming language to start with. In this book, you'll learn all the important topics that you need to know for you to implement machine learning with Python. Such topics you will meet include: An introduction and principles behind machine learning How to download, install Python, and get the best package for machine learning in Python. You'll load a dataset and understand its structure using data visualization and summaries. Getting dirty with Python The algorithms that constitute to machine learning The core foundations of data science, neural networks and deep learning The libraries you can never avoid And much more!! Python is a powerful interpreted language. Unlike other languages such as R, Python is a complete language and platform where you can apply both research and development production. Still, there are many modules and libraries which you can select from and generate different ways to perform each task. Are you ready to take upon the challenge? Good! Press the buy now button and get you copy of this book.