Adaptive Machine Learning Algorithms with PythonLearn to use adaptive algorithms to solve real-world streaming data problems. This book covers a multitude of data processing challenges, ranging from the simple to the complex. At each step, you will gain insight into real-world use cases, find solutions, explore code used to solve these problems, and create new algorithms for your own use.
Authors Chanchal Chatterjee and Vwani P. Roychowdhury begin by introducing a common framework for creating adaptive algorithms, and demonstrating how to use it to address various streaming data issues. Examples range from using matrix functions to solve machine learning and data analysis problems to more critical edge computation problems. They handle time-varying, non-stationary data with minimal compute, memory, latency, and bandwidth.
Upon finishing this book, you will have a solid understanding of how to solve adaptive machine learning and data analytics problems and be able to derive new algorithms for your own use cases. You will also c ...
Designing Machine Learning SystemsMachine learning systems are both complex and unique. Complex because they consist of many different components and involve many different stakeholders. Unique because they're data dependent, with data varying wildly from one use case to the next. In this book, you'll learn a holistic approach to designing ML systems that are reliable, scalable, maintainable, and adaptive to changing environments and business requirements.
Author Chip Huyen, co-founder of Claypot AI, considers each design decision-such as how to process and create training data, which features to use, how often to retrain models, and what to monitor-in the context of how it can help your system as a whole achieve its objectives. The iterative framework in this book uses actual case studies backed by ample references.
This book will help you tackle scenarios such as: Engineering data and choosing the right metrics to solve a business problem; Automating the process for continually developing, evaluating, deploying ...
Essential Math for Data ScienceMaster the math needed to excel in data science, machine learning, and statistics. In this book author Thomas Nield guides you through areas like calculus, probability, linear algebra, and statistics and how they apply to techniques like linear regression, logistic regression, and neural networks. Along the way you'll also gain practical insights into the state of data science and how to use those insights to maximize your career.
Learn how to: Use Python code and libraries like SymPy, NumPy, and scikit-learn to explore essential mathematical concepts like calculus, linear algebra, statistics, and machine learning; Understand techniques like linear regression, logistic regression, and neural networks in plain English, with minimal mathematical notation and jargon; Perform descriptive statistics and hypothesis testing on a dataset to interpret p-values and statistical significance; Manipulate vectors and matrices and perform matrix decomposition; Integrate and build upon incremental ...
Consul: Up and RunningWith the advent of microservices, Kubernetes, public cloud, and hybrid computing, site reliability and DevOps engineers are facing more complexity than ever before. Service mesh is an exciting new technology that promises to help tackle this complexity. A service mesh provides you with a unified control plane to manage application networking across these distinct platforms.
With this definitive guide, you'll learn how to automate networking for simple and secure application delivery with Consul.
Author Luke Kysow, Consul engineer at HashiCorp, demonstrates how this service mesh solution provides a software-driven approach to security, observability, reliability, and traffic management. Once you learn how to deploy Consul on multiple platforms, you'll be able to take control of application traffic, prevent outages, view metrics, integrate with legacy systems, and more.
Dive into the characteristics of service meshes, zero trust networking, and traffic-shaping patterns; Deploy C ...
Inside Deep LearningInside Deep Learning is an accessible guide to implementing deep learning with the PyTorch framework. It demystifies complex deep learning concepts and teaches you to understand the vocabulary of deep learning so you can keep pace in a rapidly evolving field. No detail is skipped - you'll dive into math, theory, and practical applications. Everything is clearly explained in plain English.
Deep learning doesn't have to be a black box! Knowing how your models and algorithms actually work gives you greater control over your results. And you don't have to be a mathematics expert or a senior data scientist to grasp what's going on inside a deep learning system. This book gives you the practical insight you need to understand and explain your work with confidence.
Inside Deep Learning illuminates the inner workings of deep learning algorithms in a way that even machine learning novices can understand. You'll explore deep learning concepts and tools through plain language explanations, ...
Functional Programming in KotlinFunctional Programming in Kotlin is a reworked version of the bestselling Functional Programming in Scala, with all code samples, instructions, and exercises translated into the powerful Kotlin language. In this authoritative guide, you'll take on the challenge of learning functional programming from first principles. Complex concepts are demonstrated through exercises that you'll love to test yourself against. You'll start writing Kotlin code that's easier to read, easier to reuse, better for concurrency, and less prone to bugs and errors.
Improve performance, increase maintainability, and eliminate bugs! How? By programming the functional way. Kotlin provides strong support for functional programming, taking a pragmatic approach that integrates well with OO codebases. By applying the techniques you'll learn in this book, your code will be safer, less prone to errors, and much easier to read and reuse.
Functional Programming in Kotlin teaches you how to design and write Kotlin a ...
How to Lead in Data ScienceHow to Lead in Data Science is full of techniques for leading data science at every seniority level - from heading up a single project to overseeing a whole company's data strategy. Authors Jike Chong and Yue Cathy Chang share hard-won advice that they've developed building data teams for LinkedIn, Acorns, Yiren Digital, large asset-management firms, Fortune 50 companies, and more. You'll find advice on plotting your long-term career advancement, as well as quick wins you can put into practice right away. Carefully crafted assessments and interview scenarios encourage introspection, reveal personal blind spots, and highlight development areas.
Lead your data science teams and projects to success! To make a consistent, meaningful impact as a data science leader, you must articulate technology roadmaps, plan effective project strategies, support diversity, and create a positive environment for professional growth. This book delivers the wisdom and practical skills you need to thrive a ...
R in Action, 3rd EditionR in Action, 3rd Edition makes learning R quick and easy. That's why thousands of data scientists have chosen this guide to help them master the powerful language. Far from being a dry academic tome, every example you'll encounter in this book is relevant to scientific and business developers, and helps you solve common data challenges. R expert Rob Kabacoff takes you on a crash course in statistics, from dealing with messy and incomplete data to creating stunning visualizations. This revised and expanded third edition contains fresh coverage of the new tidyverse approach to data analysis and R's state-of-the-art graphing capabilities with the ggplot2 package.
Used daily by data scientists, researchers, and quants of all types, R is the gold standard for statistical data analysis. This free and open source language includes packages for everything from advanced data visualization to deep learning. Instantly comfortable for mathematically minded users, R easily handles practical prob ...
Introducing Microsoft OrleansWelcome to Orleans, a virtual actor framework from Microsoft that allows a single developer to create immensely scalable, available applications while maintaining a high throughput. This guide is designed to give you a foundational understanding of Orleans, an overview of its implementations, and plenty of hands-on coding experience. Side-by-side monolithic and microservice patterns alongside Orleans' framework features are also discussed, to help readers without an actor model background understand how they can enhance applications.
Author Nelson's approach is to introduce patterns as needed for business requirements, including monolithic microservices and to convert monolithic to microservices, in order to keep a microservice from growing into a monolithic application. Orleans is a good choice for either of these scenarios as the next step to build your backend services and reduce unnecessary orchestration, overhead, and tooling.
The Orleans framework was designed to handle ted ...
Design and Deploy Microsoft Azure Virtual DesktopDesign and build the new desktop service from Microsoft. This book offers a modern framework, design methodology, and best practices of design and deployment for virtual apps and desktops.
Microsoft Azure Virtual Desktop (AVD) is a Desktop as a Service (DaaS) which is simple to deploy, accessible from any device, easy to manage, and secure. The book starts with AVD essentials and its critical features, followed by the planning and method of preparing for AVD. You will go through defining the requirements and assessing by setting the AVD application baseline, network requirements, and security requirements. Next, you will learn how to design and deploy the core infrastructure of Microsoft AVD to understand its Access Layer, Control Layer, Resource Layer, Hosting Layer, and User Layer. You will also learn how to design the desktop and Host Pool of AVD. And you will learn the modern way to manage and secure AVD components.
After reading this book, you will have the right blend of kn ...