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Podcasts
Learning RStudio for R Statistical Computing
Mark P.J. van der Loo, RStudio Inc, Edwin de Jonge, Mark van der Loo
Data is coming at us faster, dirtier, and at an ever increasing rate. The necessity to handle many, complex statistical analysis projects is hitting statisticians and analysts across the globe. This book will show you how to deal with it like never before, thus providing an edge and improving productivity.Learning RStudio for R Statistical Computing will teach you how to quickly and efficiently create and manage statistical analysis projects, import data, develop R scripts, and generate reports and graphics. R developers will learn about package development, coding principles, and version control with RStudio.This book will help you to learn and understand RStudio features to effectively perform statistical analysis and reporting, code editing, and R development.The book starts with a quick introduction where you will learn to load data, perform simple analysis, plot a graph, and generate automatic reports. You will then be able to explore the available features for effective coding, graphical analysis, R project management, report generation, and even project management.Learning RStudio for R Statistical Computing is stuffed with feature-rich and easy-to-understand examples, through step-by-step instructions helping you to quickly master the most popular IDE for R development.
With significant enhancements in the quality and quantity of algorithms in recent years, this second edition of Hands-On Reinforcement Learning with Python has been revamped into an example-rich guide to learning state-of-the-art reinforcement learning (RL) and deep RL algorithms with TensorFlow 2 and the OpenAI Gym toolkit.In addition to exploring RL basics and foundational concepts such as Bellman equation, Markov decision processes, and dynamic programming algorithms, this second edition dives deep into the full spectrum of value-based, policy-based, and actor-critic RL methods. It explores state-of-the-art algorithms such as DQN, TRPO, PPO and ACKTR, DDPG, TD3, and SAC in depth, demystifying the underlying math and demonstrating implementations through simple code examples.The book has several new chapters dedicated to new RL techniques, including distributional RL, imitation learning, inverse RL, and meta RL. You will learn to leverage stable baselines, an improvement of OpenAI’s baseline library, to effortlessly implement popular RL algorithms. The book concludes with an overview of promising approaches such as meta-learning and imagination augmented agents in research.By the end, you will become skilled in effectively employing RL and deep RL in your real-world projects.
Go Programming – From Beginner to Professional is a comprehensive guide that takes your proficiency in the Go programming language from novice to expert. Starting with fundamental concepts, this book covers variables, command-line tools, and working with data before delving into advanced concepts, including error handling, interfaces, and generics, harnessing Go’s latest features through hands-on exercises. Along the way, you’ll learn to structure projects using Go modules, manage packages effectively, and master debugging techniques.As you progress, you’ll get to grips with practical application-centric aspects such as command-line programming, file manipulation, and working with SQL databases. Additionally, the book explores web server development, RESTful APIs, and utilizing the Go HTTP client to interact with web applications. Further enhancing your Go skills, you’ll learn concurrent programming, testing methodologies, Go tools, and how to deploy applications in the cloud. Throughout the book, you’ll uncover Go’s hidden gems and gain insights into time manipulation, best practices, and more.By the end of this book, you’ll have worked through practical exercises and activities that’ll equip you with the knowledge and skills needed to excel as a proficient Go developer, primed for success in real-world projects.
Oracle UCM is a world-leading Enterprise Content Management platform. From Document Management, Web, Records, and more—Oracle has got all your business needs covered. Oracle UCM enables your organization to efficiently manage, store, preserve, and deliver content and documents.Written by Oracle ACE Dmitri Khanine, this book is a complete practical guide to building an ECM system and successfully configuring, administering, and operating it. It also shows you how to efficiently manage your organization's content and customize the UCM to fit your needs.This book wastes no time in getting you up and running and dives straight into the installation of the content server in Chapter 1. In the second chapter, you will master all the major controls and the admin interface. Metadata—a very important ingredient of any ECM—is thoroughly covered in Chapter 3. The book then moves on to the important tasks of securing your ECM system, configuring and managing workflows, and understanding and implementing virtual folders. The book also gives you an under-the-hood view of Stellent in Chapter 7. In the later chapters, you will learn how to migrate content like a pro and easily customize Oracle ECM. A bonus addition to the book is the final chapter, which is an easy-to-follow primer on web content management.
Practical Data Analysis. Pandas, MongoDB, Apache Spark, and more - Second Edition
Beyond buzzwords like Big Data or Data Science, there are a great opportunities to innovate in many businesses using data analysis to get data-driven products. Data analysis involves asking many questions about data in order to discover insights and generate value for a product or a service.This book explains the basic data algorithms without the theoretical jargon, and you’ll get hands-on turning data into insights using machine learning techniques. We will perform data-driven innovation processing for several types of data such as text, Images, social network graphs, documents, and time series, showing you how to implement large data processing with MongoDB and Apache Spark.
Anthony So, Thomas V. Joseph, Robert Thas John, Andrew Worsley, ...
Where there’s data, there’s insight. With so much data being generated, there is immense scope to extract meaningful information that’ll boost business productivity and profitability. By learning to convert raw data into game-changing insights, you’ll open new career paths and opportunities.The Data Science Workshop begins by introducing different types of projects and showing you how to incorporate machine learning algorithms in them. You’ll learn to select a relevant metric and even assess the performance of your model. To tune the hyperparameters of an algorithm and improve its accuracy, you’ll get hands-on with approaches such as grid search and random search.Next, you’ll learn dimensionality reduction techniques to easily handle many variables at once, before exploring how to use model ensembling techniques and create new features to enhance model performance. In a bid to help you automatically create new features that improve your model, the book demonstrates how to use the automated feature engineering tool. You’ll also understand how to use the orchestration and scheduling workflow to deploy machine learning models in batch.By the end of this book, you’ll have the skills to start working on data science projects confidently. By the end of this book, you’ll have the skills to start working on data science projects confidently.
While Salesforce is a powerful platform, it is prone to common pitfalls that can result in suboptimal performance, increased costs, and reduced user satisfaction. Known as anti-patterns, these problems can arise from design flaws, poor implementation choices, or a lack of understanding of best practices.Written by a seasoned Salesforce professional and 33-time certified Salesforce Certified Technical Architect, this revised edition will teach you how to identify and avoid common issues, optimize your Salesforce architecture, and ensure successful implementation. This second edition is updated with a comprehensive exploration of Salesforce, along with the addition of the most common Salesforce anti-patterns, providing in-depth analysis and practical solutions. These key learnings will further refine your skills to help you build more robust, scalable, and efficient Salesforce architectures. The chapters offer an expanded coverage of emerging technology trends such as AI and DevOps, updated examples, and additional case studies to ensure that you have the latest information and insights.By the end of this book, you’ll have gained the confidence and expertise needed to design and implement effective Salesforce solutions.