Build stylish, slick, and speedy-to-load user interfaces in React without writing custom classes. React Hooks are a new category of functions that help you to manage state, lifecycle, and side effects within functional components. React Hooks in Action teaches you to use pre-built hooks like useState, useReducer and useEffect to build your own hooks. Your code will be more reusable, require less boilerplate, and you’ll instantly be a more effective React developer.
Build stylish, slick, and speedy-to-load user interfaces in React without writing custom classes. React Hooks are a new category of functions that help you to manage state,…
Your brain responds in a predictable way when it encounters new or difficult tasks. This unique book teaches you concrete techniques rooted in cognitive science that will improve the way you learn and think about code.
In The Programmer’s Brain: What every programmer needs to know about cognition you will learn:
- Fast and effective ways to master new programming languages
- Speed reading skills to quickly comprehend new code
- Techniques to unravel the meaning of complex code
- Ways to learn new syntax and keep it memorized
- Writing code that is easy for others to read
- Picking the right names for your variables
- Making your codebase more understandable to newcomers
- Onboarding new developers to your team
Learn how to optimize your brain’s natural cognitive processes to read code more easily, write code faster, and pick up new languages in much less time. This book will help you through the confusion you feel when faced with strange and complex code, and explain a codebase in ways that can make a new team member productive in days!
Your brain responds in a predictable way when it encounters new or difficult tasks. This unique book teaches you concrete techniques rooted in cognitive science that will improve…
Computer science theory quickly collides with the harsh reality of professional software development. This wickedly smart and devilishly funny beginner's guide shows you how to get the job done by prioritizing tasks, making quick decisions, and knowing which rules to break.
In Street Coder you will learn:
Data types, algorithms, and data structures for speedy software development
Putting "bad" practices to good use
Learn to love testing
Embrace code breaks and become friends with failure
Beginner-friendly insight on code optimization, asynchronous programming, parallelization, and refactoring
Street Coder: Rules to break and how to break them is a programmer's survival guide, full of tips, tricks, and hacks that will make you a more efficient programmer. It takes the best practices you learn in a computer science class and deconstructs them to show when they’re beneficial—and when they aren't!
This book's rebel mindset challenges status quo thinking and exposes the important skills you need on the job. You'll learn the crucial importance of algorithms and data structures, turn programming chores into programming pleasures, and shatter dogmatic principles keeping you from your full potential. Welcome to the streets!
Computer science theory quickly collides with the harsh reality of professional software development. This wickedly smart and devilishly funny beginner's guide shows you how to…
Most machine learning systems that are deployed in the world today learn from human feedback. However, most machine learning courses focus almost exclusively on the algorithms, not the human-computer interaction part of the systems. This can leave a big knowledge gap for data scientists working in real-world machine learning, where data scientists spend more time on data management than on building algorithms. Human-in-the-Loop Machine Learning is a practical guide to optimizing the entire machine learning process, including techniques for annotation, active learning, transfer learning, and using machine learning to optimize every step of the process.
Most machine learning systems that are deployed in the world today learn from human feedback. However, most machine learning courses focus almost exclusively on the algorithms,…
Graph-Powered Machine Learning teaches you how to exploit the natural relationships in structured and unstructured datasets using graph-oriented machine learning algorithms and tools. In this authoritative book, you’ll master the architectures and design practices of graphs, and avoid common pitfalls. Author Alessandro Negro explores examples from real-world applications that connect GraphML concepts to real world tasks.
Graph-Powered Machine Learning teaches you how to exploit the natural relationships in structured and unstructured datasets using graph-oriented machine learning algorithms and…
Learn Quantum Computing with Python and Q# demystifies quantum computing. Using Python and the new quantum programming language Q#, you’ll build your own quantum simulator and apply quantum programming techniques to real-world examples including cryptography and chemical analysis.
Quantum computers present a radical leap in speed and computing power. Improved scientific simulations and new frontiers in cryptography that are impossible with classical computing may soon be in reach. Microsoft’s Quantum Development Kit and the Q# language give you the tools to experiment with quantum computing without knowing advanced math or theoretical physics.
Learn Quantum Computing with Python and Q# introduces quantum computing from a practical perspective. Use Python to build your own quantum simulator and take advantage of Microsoft’s open source tools to fine-tune quantum algorithms. The authors explain complex math and theory through stories, visuals, and games. You’ll learn to apply quantum to real-world applications, such as sending secret messages and solving chemistry problems.
Learn Quantum Computing with Python and Q# demystifies quantum computing. Using Python and the new quantum programming language Q#, you’ll build your own quantum simulator and…
Haskell in Depth unlocks a new level of skill with this challenging language. Going beyond the basics of syntax and structure, this book opens up critical topics like advanced types, concurrency, and data processing.
Summary
Turn the corner from “Haskell student” to “Haskell developer.” Haskell in Depth explores the important language features and programming skills you’ll need to build production-quality software using Haskell. And along the way, you’ll pick up some interesting insights into why Haskell looks and works the way it does. Get ready to go deep!
Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
About the technology
Software for high-precision tasks like financial transactions, defense systems, and scientific research must be absolutely, provably correct. As a purely functional programming language, Haskell enforces a mathematically rigorous approach that can lead to concise, efficient, and bug-free code. To write such code you’ll need deep understanding. You can get it from this book!
About the book
Haskell in Depth unlocks a new level of skill with this challenging language. Going beyond the basics of syntax and structure, this book opens up critical topics like advanced types, concurrency, and data processing. You’ll discover key parts of the Haskell ecosystem and master core design patterns that will transform how you write software.
What's inside
- Building applications, web services, and networking apps
- Using sophisticated libraries like lens, singletons, and servant
- Organizing projects with Cabal and Stack
- Error-handling and testing
- Pure parallelism for multicore processors
Haskell in Depth unlocks a new level of skill with this challenging language. Going beyond the basics of syntax and structure, this book opens up critical topics like advanced…
You are going to need more than technical knowledge to succeed as a data scientist. Build a Career in Data Science teaches you what school leaves out, from how to land your first job to the lifecycle of a data science project, and even how to become a manager.
What are the keys to a data scientist’s long-term success? Blending your technical know-how with the right “soft skills” turns out to be a central ingredient of a rewarding career.
about the book
Build a Career in Data Science is your guide to landing your first data science job and developing into a valued senior employee. By following clear and simple instructions, you’ll learn to craft an amazing resume and ace your interviews. In this demanding, rapidly changing field, it can be challenging to keep projects on track, adapt to company needs, and manage tricky stakeholders. You’ll love the insights on how to handle expectations, deal with failures, and plan your career path in the stories from seasoned data scientists included in the book.
You are going to need more than technical knowledge to succeed as a data scientist. Build a Career in Data Science teaches you what school leaves out, from how to land your first…
The mathematical paradigms that underlie deep learning typically start out as hard-to-read academic papers, often leaving engineers in the dark about how their models actually function. Math and Architectures of Deep Learning bridges the gap between theory and practice, laying out the math of deep learning side by side with practical implementations in Python and PyTorch. Written by deep learning expert Krishnendu Chaudhury, you’ll peer inside the “black box” to understand how your code is working, and learn to comprehend cutting-edge research you can turn into practical applications.
about the technology
It’s important to understand how your deep learning models work, both so that you can maintain them efficiently and explain them to other stakeholders. Learning mathematical foundations and neural network architecture can be challenging, but the payoff is big. You’ll be free from blind reliance on prepackaged DL models and able to build, customize, and re-architect for your specific needs. And when things go wrong, you’ll be glad you can quickly identify and fix problems.
about the book
Math and Architectures of Deep Learning sets out the foundations of DL in a way that’s both useful and accessible to working practitioners. Each chapter explores a new fundamental DL concept or architectural pattern, explaining the underpinning mathematics and demonstrating how they work in practice with well-annotated Python code. You’ll start with a primer of basic algebra, calculus, and statistics, working your way up to state-of-the-art DL paradigms taken from the latest research. By the time you’re done, you’ll have a combined theoretical insight and practical skills to identify and implement DL architecture for almost any real-world challenge.
The mathematical paradigms that underlie deep learning typically start out as hard-to-read academic papers, often leaving engineers in the dark about how their models actually…
Probabilistic Deep Learning: With Python, Keras and TensorFlow Probability teaches the increasingly popular probabilistic approach to deep learning that allows you to refine your results more quickly and accurately without much trial-and-error testing. Emphasizing practical techniques that use the Python-based Tensorflow Probability Framework, you’ll learn to build highly-performant deep learning applications that can reliably handle the noise and uncertainty of real-world data.
The world is a noisy and uncertain place. Probabilistic deep learning models capture that noise and uncertainty, pulling it into real-world scenarios. Crucial for self-driving cars and scientific testing, these techniques help deep learning engineers assess the accuracy of their results, spot errors, and improve their understanding of how algorithms work.
Probabilistic Deep Learning is a hands-on guide to the principles that support neural networks. Learn to improve network performance with the right distribution for different data types, and discover Bayesian variants that can state their own uncertainty to increase accuracy. This book provides easy-to-apply code and uses popular frameworks to keep you focused on practical applications.
Probabilistic Deep Learning: With Python, Keras and TensorFlow Probability teaches the increasingly popular probabilistic approach to deep learning that allows you to refine your…
Deep Learning with PyTorch teaches you to create neural networks and deep learning systems with PyTorch. This practical book quickly gets you to work building a real-world example from scratch: a tumor image classifier. Along the way, it covers best practices for the entire DL pipeline, including the PyTorch Tensor API, loading data in Python, monitoring training, and visualizing results. After covering the basics, the book will take you on a journey through larger projects. The centerpiece of the book is a neural network designed for cancer detection. You'll discover ways for training networks with limited inputs and start processing data to get some results. You'll sift through the unreliable initial results and focus on how to diagnose and fix the problems in your neural network. Finally, you'll look at ways to improve your results by training with augmented data, make improvements to the model architecture, and perform other fine tuning.
Deep Learning with PyTorch teaches you to create neural networks and deep learning systems with PyTorch. This practical book quickly gets you to work building a real-world example…
Many AI projects are in progress today, and many of them will fail. This book helps you avoid starting an AI project that's doomed to failure and shows you how to lead the right AI project toward the business results.
Conventional wisdom tells us that the determinant of success or failure of an AI project is the project team's in-depth knowledge of AI technology. It is not. Overfocus on technology, paired with a vague understanding of the actions leaders must take for their AI projects to succeed, causes unrealistic expectations and poor business results. Believing that success with AI is determined solely by technical prowess confounds an enabler with a capability. Although you do need to have technical skills on your team for your AI project to succeed technically, to implement AI in your business, you also need to link technology with business goals. Only humans can do that, and this book shows you how.
Succeeding with AI helps you make your AI projects predictable, successful, and profitable. It's filled with practical techniques for running AI projects that ensure they're cost-effective and focused on the right business goals.
Many AI projects are in progress today, and many of them will fail. This book helps you avoid starting an AI project that's doomed to failure and shows you how to lead the right…
The Spark distributed data processing platform provides an easy-to-implement tool for ingesting, streaming, and processing data from any source. In Spark in Action, Second Edition, you’ll learn to take advantage of Spark’s core features and incredible processing speed, with applications including real-time computation, delayed evaluation, and machine learning. Spark skills are a hot commodity in enterprises worldwide, and with Spark’s powerful and flexible Java APIs, you can reap all the benefits without first learning Scala or Hadoop.
The Spark distributed data processing platform provides an easy-to-implement tool for ingesting, streaming, and processing data from any source. In Spark in Action, Second…
Professional developers know the many benefits of writing application code that’s clean, well-organized, and easy to maintain. By learning and following established patterns and best practices, you can take your code and your career to a new level.
With Practices of the Python Pro, you’ll learn to design professional-level, clean, easily maintainable software at scale using the incredibly popular programming language, Python. You’ll find easy-to-grok examples that use pseudocode and Python to introduce software development best practices, along with dozens of instantly useful techniques that will help you code like a pro.
Professional developers know the many benefits of writing application code that’s clean, well-organized, and easy to maintain. By learning and following established patterns and…
Kafka in Action is a practical, hands-on guide to building Kafka-based data pipelines. Filled with real-world use cases and scenarios, this book probes Kafka's most common use cases, ranging from simple logging through managing streaming data systems for message routing, analytics, and more.
In systems that handle big data, streaming data, or fast data, it's important to get your data pipelines right. Apache Kafka is a wicked-fast distributed streaming platform that operates as more than just a persistent log or a flexible message queue.
Kafka in Action is a practical, hands-on guide to building Kafka-based data pipelines. Filled with real-world use cases and scenarios, this book probes Kafka's most common use…
Humans do a great job of reading text, identifying key ideas, summarizing, making connections, and other tasks that require comprehension and context. Recent advances in deep learning make it possible for computer systems to achieve similar results. Deep Learning for Natural Language Processing teaches you to apply deep learning methods to natural language processing (NLP) to interpret and use text effectively. In this insightful book, NLP expert Stephan Raaijmakers distills his extensive knowledge of the latest state-of-the-art developments in this rapidly emerging field. Through detailed instruction and abundant code examples, you’ll explore the most challenging NLP issues and learn how to solve them with deep learning!
Humans do a great job of reading text, identifying key ideas, summarizing, making connections, and other tasks that require comprehension and context. Recent advances in deep…
HTTP/2 in Action is a complete guide to HTTP/2, one of the core protocols of the web. Because HTTP/2 has been designed to be easy to transition to, including keeping it backwards compatible, adoption is rapid and expected to increase over the next few years. Concentrating on practical matters, this interesting book presents key HTTP/2 concepts such as frames, streams, and multiplexing and explores how they affect the performance and behavior of your websites.
About the technology
HTTP—Hypertext Transfer Protocol—is the standard for exchanging messages between websites and browsers. And after 20 years, it's gotten a much-needed upgrade. With support for streams, server push, header compression, and prioritization, HTTP/2 delivers vast improvements in speed, security, and efficiency.
About the book
HTTP/2 in Action teaches you everything you need to know to use HTTP/2 effectively. You'll learn how to optimize web performance with new features like frames, multiplexing, and push. You'll also explore real-world examples on advanced topics like flow control and dependencies. With ready-to-implement tips and best practices, this practical guide is sure to get you—and your websites—up to speed!
HTTP/2 in Action is a complete guide to HTTP/2, one of the core protocols of the web. Because HTTP/2 has been designed to be easy to transition to, including keeping it backwards…
Type-related failures are common and can be very costly. Famously, in 1999, NASA's Mars Climate Orbiter burned up in the atmosphere because of an error that could have easily been prevented with typing. By taking advantage of the strong type systems available in most modern programming languages, you can eliminate whole classes of errors.
Programming with Types teaches you type system techniques for writing software that's safe, correct, easy to test and maintain, and that practically documents itself. Master these techniques, and you may even help prevent an interstellar catastrophe!
Type-related failures are common and can be very costly. Famously, in 1999, NASA's Mars Climate Orbiter burned up in the atmosphere because of an error that could have easily been…
Unit Testing Principles, Patterns and Practices shows you how to refine your existing unit tests by implementing modern best practices. You’ll learn to spot which tests are performing, which need refactoring, and which need to be deleted entirely! Upgrade your testing suite with new testing styles, good patterns, and reliable automated testing.
Unit Testing Principles, Patterns and Practices shows you how to refine your existing unit tests by implementing modern best practices. You’ll learn to spot which tests are…
