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Programming Machine Learning : From Coding to Deep Learning
You've decided to tackle machine learning - because you're job hunting, embarking on a new project, or just think self-driving cars are cool.But where to start? It's easy to be intimidated, even as a software developer.The good news is that it doesn't have to be that hard.Master machine learning by writing code one line at a time, from simple learning programs all the way to a true deep learning system.Tackle the hard topics by breaking them down so they're easier to understand, and build your confidence by getting your hands dirty.Peel away the obscurities of machine learning, starting from scratch and going all the way to deep learning.Machine learning can be intimidating, with its reliance on math and algorithms that most programmers don't encounter in their regular work.Take a hands-on approach, writing the Python code yourself, without any libraries to obscure what's really going on.Iterate on your design, and add layers of complexity as you go.Build an image recognition application from scratch with supervised learning.Predict the future with linear regression. Dive into gradient descent, a fundamental algorithm that drives most of machine learning.Create perceptrons to classify data. Build neural networks to tackle more complex and sophisticated data sets.Train and refine those networks with backpropagation and batching.Layer the neural networks, eliminate overfitting, and add convolution to transform your neural network into a true deep learning system.Start from the beginning and code your way to machine learning mastery.What You Need: The examples in this book are written in Python, but don't worry if you don't know this language: you'll pick up all the Python you need very quickly.Apart from that, you'll only need your computer, and your code-adept brain.
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Effective Software Development for the Enterprise : Beyond Domain Driven Design, Software Architecture, and Extreme Programming
It’s a jungle out there. Delivering software solutions with predictable costs, time, scope, and quality has become more complicated than ever.Developers need to account for multiple moving targets, including often avoided but always relevant factors such as culture, people, and leadership.To effectively deal with these challenges, it’s necessary to rethink the entire delivery chain of modern software development.This book addresses all these topics, putting everything in perspective, from the potential awkwardness created by cultural differences to connecting code with business outcomes to make delivering quality solutions possible.As a software engineer who strives to be his best and challenge the status quo when building IT systems, author Tengiz Tutisani always wanted a book that would cover all of these elements from a developer’s perspective — so he wrote one.Effective Software Development for the Enterprise builds on advanced disciplines, methodologies, and techniques derived from domain-driven design, software architecture, and extreme programming.Its objective is to aid modern software engineers and solution architects in building and delivering high-quality solutions for an enterprise while meeting ambitious criteria:Meet users' expectationsDeliver solutions on time with no defectsCreate products that can scale-out horizontallySolutions should not require a dedicated production support teamAccelerate development paceDouble ROI per developer, team, and softwareYou will learn how to achieve these objectives in any engineering environment by developing solid strategies based on the industry's well-known, recognized, and proven patterns and principles.After reading this book, you will be ready to effectively deal with any and all challenges posed by today’s hyper-competitive, globally-diverse, fast-moving enterprise environment. Who This Book Is ForProfessional software engineers and solution architects, as well as those aspiring to become one.Additionally, software engineering leaders will benefit from reading it, as it will help them maximize their impact via successful software project deliveries.
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Agile Software Development
Agile Software Development is an introduction to agile software development methods.Agile methods try to diminish complexity, increase transparency, and reach a deployable product in a shorter time frame.Agile methods use an iterative and incremental approach to minimize risks and to avoid maldevelopment.The book gives a short introduction to agile methods and agile software development principles.It serves as a study book and as a reference manual.Based on the official Scrum Guide, the book also covers other topics such as best practices for agile software development and agile testing.It targets practitioners who want to start with agile software development, as well as developers or project managers who already use agile methodologies.The book can be read from the beginning, but each chapter has been written in a way so it can be read individually.
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Coding Club Python: Programming Art Supplement 1
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Software development is becoming recognised more and more as an essential skill and profession in today's increasingly digital world.This book is a pragmatic guide to software development in practice.It explores the inner workings of software development in the context of the industry, covering good practice for software developers and providing you with tools and practical understanding you'll need to advance within the software development world.
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Learning Object-Oriented Programming
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Coding Literacy : How Computer Programming Is Changing Writing
How the theoretical tools of literacy help us understand programming in its historical, social and conceptual contexts. The message from educators, the tech community, and even politicians is clear: everyone should learn to code.To emphasize the universality and importance of computer programming, promoters of coding for everyone often invoke the concept of "literacy," drawing parallels between reading and writing code and reading and writing text.In this book, Annette Vee examines the coding-as-literacy analogy and argues that it can be an apt rhetorical frame.The theoretical tools of literacy help us understand programming beyond a technical level, and in its historical, social, and conceptual contexts.Viewing programming from the perspective of literacy and literacy from the perspective of programming, she argues, shifts our understandings of both.Computer programming becomes part of an array of communication skills important in everyday life, and literacy, augmented by programming, becomes more capacious. Vee examines the ways that programming is linked with literacy in coding literacy campaigns, considering the ideologies that accompany this coupling, and she looks at how both writing and programming encode and distribute information.She explores historical parallels between writing and programming, using the evolution of mass textual literacy to shed light on the trajectory of code from military and government infrastructure to large-scale businesses to personal use.Writing and coding were institutionalized, domesticated, and then established as a basis for literacy.Just as societies demonstrated a "literate mentality" regardless of the literate status of individuals, Vee argues, a "computational mentality" is now emerging even though coding is still a specialized skill.
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