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Machine Learning with R Quick Start Guide. A beginner's guide to implementing machine learning techniques from scratch using R 3.5

Iván Pastor Sanz

Machine Learning with R Quick Start Guide takes you on a data-driven journey that starts with the very basics of R and machine learning. It gradually builds upon core concepts so you can handle the varied complexities of data and understand each stage of the machine learning pipeline.From data collection to implementing Natural Language Processing (NLP), this book covers it all. You will implement key machine learning algorithms to understand how they are used to build smart models. You will cover tasks such as clustering, logistic regressions, random forests, support vector machines, and more. Furthermore, you will also look at more advanced aspects such as training neural networks and topic modeling.By the end of the book, you will be able to apply the concepts of machine learning, deal with data-related problems, and solve them using the powerful yet simple language that is R.

Machine Learning with R. R gives you access to the cutting-edge software you need to prepare data for machine learning. No previous knowledge required – this book will take you methodically through every stage of applying machine learning

Brett Lantz

Machine learning, at its core, is concerned with transforming data into actionable knowledge. This fact makes machine learning well-suited to the present-day era of big data and data science. Given the growing prominence of R—a cross-platform, zero-cost statistical programming environment—there has never been a better time to start applying machine learning. Whether you are new to data science or a veteran, machine learning with R offers a powerful set of methods for quickly and easily gaining insight from your data.Machine Learning with R is a practical tutorial that uses hands-on examples to step through real-world application of machine learning. Without shying away from the technical details, we will explore Machine Learning with R using clear and practical examples. Well-suited to machine learning beginners or those with experience. Explore R to find the answer to all of your questions.How can we use machine learning to transform data into action? Using practical examples, we will explore how to prepare data for analysis, choose a machine learning method, and measure the success of the process.We will learn how to apply machine learning methods to a variety of common tasks including classification, prediction, forecasting, market basket analysis, and clustering. By applying the most effective machine learning methods to real-world problems, you will gain hands-on experience that will transform the way you think about data.Machine Learning with R will provide you with the analytical tools you need to quickly gain insight from complex data.

Machine Learning with Spark. Develop intelligent, distributed machine learning systems - Second Edition

Rajdeep Dua, Manpreet Singh Ghotra

This book will teach you about popular machine learning algorithms and their implementation. You will learn how various machine learning concepts are implemented in the context of Spark ML. You will start by installing Spark in a single and multinode cluster. Next you'll see how to execute Scala and Python based programs for Spark ML. Then we will take a few datasets and go deeper into clustering, classification, and regression. Toward the end, we will also cover text processing using Spark ML.Once you have learned the concepts, they can be applied to implement algorithms in either green-field implementations or to migrate existing systems to this new platform. You can migrate from Mahout or Scikit to use Spark ML.By the end of this book, you will acquire the skills to leverage Spark's features to create your own scalable machine learning applications and power a modern data-driven business.

Machine Learning with Swift. Artificial Intelligence for iOS

Alexander Sosnovshchenko, Oleksandr Baiev

Machine learning as a field promises to bring increased intelligence to the software by helping us learn and analyse information efficiently and discover certain patterns that humans cannot. This book will be your guide as you embark on an exciting journey in machine learning using the popular Swift language. We’ll start with machine learning basics in the first part of the book to develop a lasting intuition about fundamental machine learning concepts. We explore various supervised and unsupervised statistical learning techniques and how to implement them in Swift, while the third section walks you through deep learning techniques with the help of typical real-world cases. In the last section, we will dive into some hard core topics such as model compression, GPU acceleration and provide some recommendations to avoid common mistakes during machine learning application development. By the end of the book, you'll be able to develop intelligent applications written in Swift that can learn for themselves.

Machine Learning with TensorFlow 1.x. Second generation machine learning with Google's brainchild - TensorFlow 1.x

Saif Ahmed, Quan Hua, Shams Ul Azeem

Google's TensorFlow is a game changer in the world of machine learning. It has made machine learning faster, simpler, and more accessible than ever before. This book will teach you how to easily get started with machine learning using the power of Python and TensorFlow 1.x. Firstly, you’ll cover the basic installation procedure and explore the capabilities of TensorFlow 1.x. This is followed by training and running the first classifier, and coverage of the unique features of the library including data ?ow graphs, training, and the visualization of performance with TensorBoard—all within an example-rich context using problems from multiple industries. You’ll be able to further explore text and image analysis, and be introduced to CNN models and their setup in TensorFlow 1.x. Next, you’ll implement a complete real-life production system from training to serving a deep learning model. As you advance you’ll learn about Amazon Web Services (AWS) and create a deep neural network to solve a video action recognition problem. Lastly, you’ll convert the Caffe model to TensorFlow and be introduced to the high-level TensorFlow library, TensorFlow-Slim.By the end of this book, you will be geared up to take on any challenges of implementing TensorFlow 1.x in your machine learning environment.

Machine Learning with the Elastic Stack. Expert techniques to integrate machine learning with distributed search and analytics

Rich Collier, Bahaaldine Azarmi

Machine Learning with the Elastic Stack is a comprehensive overview of the embedded commercial features of anomaly detection and forecasting. The book starts with installing and setting up Elastic Stack. You will perform time series analysis on varied kinds of data, such as log files, network flows, application metrics, and financial data.As you progress through the chapters, you will deploy machine learning within the Elastic Stack for logging, security, and metrics. In the concluding chapters, you will see how machine learning jobs can be automatically distributed and managed across the Elasticsearch cluster and made resilient to failure.By the end of this book, you will understand the performance aspects of incorporating machine learning within the Elastic ecosystem and create anomaly detection jobs and view results from Kibana directly.

Magento 1.3 Sales Tactics Cookbook. Solve real-world Magento sales problems with a collection of simple but effective recipes

Roy Rubin, William Rice, William Rice

Magento is a feature-rich, professional open source e-commerce solution that offers users complete flexibility and control over the look, content, and functionality of their online store. Although Magento provides users with the power to create dynamic e-commerce sites, it can be challenging to get beyond the basics and create sites that are tailored to your unique business needs.This book gives you a hands-on experience on Magento, helping you increase your revenue by implementing proven sales tactics on your Magento site.This book contains techniques to help you with each stage of selling to your customers: attracting visitors, driving them to your product pages, making the sale, increasing sales, engaging your customers, and more. It contains a powerful mix of techniques for increasing sales in your online storefront. Over thirty of the techniques are short and stand alone. A few are designed to be used together, such as the seven techniques in the chapter on creating an international storefront. Some techniques make creative use of Magento’s standard features. A few techniques combine Magento with other tools, such as social networking sites. All the techniques are explained in clear, step-by-step directions, with many screenshots. The book uses an example site for each technique, so that you can see exactly how it will affect your storefront. You can jump into the book at any point, or, work through it from beginning to end.

Magento 2 Beginners Guide. Discover what you need to know to build your own profitable online stores using the power of Magento 2!

Gabriel Guarino

Do you have a good product to sell but need your start-up to sell it to your potential customers the right way? Were you unhappy with what Magento 1 had to offer and are looking forward to trying out what Magento 2 provides? If either of these questions ring a bell, then this book is for you! You'll start by getting a general understanding of what Magento is, why and how you should use it, and whether it is possible and feasible to migrate from an old web store to Magento 2.We'll introduce you to the main e-commerce concepts and basic features and let you play with them, so you can get a taste of how catalog and content management works. Following on from that, we'll show you how to tune your store up. You will learn how to get web store offers up and running, how to offer various discounts in the catalog, how to let the customers reduce the total price in the shopping cart by combining different products, and how to generate coupon codes that customers can use. Finally, we'll get serious and turn your plaything into a real web store, teaching you how to run it for real.