Programowanie
Niezależnie czy dopiero rozpoczynacie swoją przygodę z programowaniem, czy jesteście już uznanymi na rynku profesjonalistami, to w kategorii Programowanie na pewno znajdziecie podręczniki, które pomogą Wam w przebiegu pracy, czy też w nauce podstaw programowania.
W książkach z tego działu zawarta jest wiedza zarówno związana z czysto technicznymi sprawami typu składnia języków, ale także z umiejętnościami bardziej "miękkimi" jak obsługa i wykorzystanie pełnych możliwości środowisk programistycznych, czy też projektowanie oprogramowania lub metody numeryczne czy oraz struktury danych.
Joshua Alan Teter, Ben Tobin
The technical program manager (TPM) is a relatively new role born out of the need of the tech industry to have a specialized practitioner who speaks both tech and business and leverages this bilingual talent to get results that no one else can.This book dives into what makes a TPM tick. You’ll find out which project and program management skills will help you shine and how you can apply your technical skills for effective results. This book looks at the TPM role across the Big Five tech companies (Amazon, Google, Microsoft, Apple, and Meta) to help you discern the most effective skills to be successful no matter which company you work for.Are you already a well-performing TPM looking to see what’s next? This book identifies the career paths for a TPM at the Big Five to help you decide the next step for you.By the end of this book, you’ll have a clear understanding of how to be a TPM, along with a breakdown of the necessary technical and program management skills to develop a clear roadmap for your career.
Technologiada. Młodzi kompetentni
Piotr Synowiec
Doświadczyć znaczy zrozumieć Świat biegnie do przodu coraz szybciej i szybciej, w rytmie, w jakim rozwija się ludzka wiedza i technologia, jaka dzięki niej powstaje. Z jednej strony to świetnie - kto czterdzieści lat temu przypuszczał, że nosić będzie w kieszeni mały, supersprawny i wszechwiedzący komputer, dla niepoznaki zwany "telefonem"? Z drugiej, to trochę przerażające. Ciężko nadążyć. Bo choć większość z nas, starszych i młodszych, na co dzień korzysta z nowoczesnych technologii, to jednak rzadko kto je naprawdę rozumie. Bo żeby zrozumieć, żeby się nauczyć i móc pójść dalej, trzeba spróbować: zaprojektować trójwymiarowy obiekt w programie pCon.planner zbudować silnik z klocków LEGO stworzyć animację, a może i grę w Scratchu Potem można ruszyć do przodu. Na ścieżkę twórców, odkrywców, naukowców i inżynierów na miarę XXI wieku. Potem można dorosnąć i przemienić pasję w pracę. Najpierw jednak trzeba sięgnąć do zasobów nieograniczonej w młodym wieku wyobraźni i połączyć ją z możliwościami, jakie daje nam dzisiejszy świat, już teraz pukający do drzwi przyszłości. Z niewielką pomocą tej książki Twoje nastoletnie dziecko bawiąc się aplikacjami i narzędziami dostępnymi na wyciągnięcie ręki i kliknięcie myszką, opanuje umiejętności, które mogą okazać się kluczowe dla jego przyszłego życia. Podaruj mu Technologiadę, a wraz z nią kompetencje przyszłości!
Ahilan Ponnusamy, Andreas Spanner, Mirco Hering, Vincent...
Cloud goals, such as faster time to market, lower total cost of ownership (TCO), capex reduction, self-service enablement, and complexity reduction are important, but organizations often struggle to achieve the desired outcomes. With edge computing gaining momentum across industries and making it possible to move workloads seamlessly between cloud and edge locations, organizations need working recipes to find ways of extracting the most value out of their cloud and edge estate.This book provides a practical way to build a strategy-aligned operating model while considering various related factors such as culture, leadership, team structures, metrics, intrinsic motivators, team incentives, tenant experience, platform engineering, operations, open source, and technology choices. Throughout the chapters, you’ll discover how single, hybrid, or multicloud architectures, security models, automation, application development, workload deployments, and application modernization can be reutilized for edge workloads to help you build a secure yet flexible technology operating model. The book also includes a case study which will walk you through the operating model build process in a step-by-step way.By the end of this book, you’ll be able to build your own fit-for-purpose distributed technology operating model for your organization in an open culture way.
Marius Bancila
Learn how the metaprogramming technique enables you to create data structures and functions that allow computation to happen at compile time. With this book, you'll realize how templates help you avoid writing duplicate code and are key to creating generic libraries, such as the standard library or Boost, that can be used in a multitude of programs.The introductory chapters of this book will give you insights into the fundamentals of templates and metaprogramming. You'll then move on to practice writing complex templates and exploring advanced concepts such as template recursion, template argument deduction, forwarding references, type traits, and conditional compilation. Along the way, you'll learn how to write variadic templates and how to provide requirements to the template arguments with C++20 constraints and concepts. Finally, you'll apply your knowledge of C++ metaprogramming templates to implement various metaprogramming patterns and techniques.By the end of this book, you'll have learned how to write effective templates and implement metaprogramming in your everyday programming journey.
Palanisamy P
With deep reinforcement learning, you can build intelligent agents, products, and services that can go beyond computer vision or perception to perform actions. TensorFlow 2.x is the latest major release of the most popular deep learning framework used to develop and train deep neural networks (DNNs). This book contains easy-to-follow recipes for leveraging TensorFlow 2.x to develop artificial intelligence applications.Starting with an introduction to the fundamentals of deep reinforcement learning and TensorFlow 2.x, the book covers OpenAI Gym, model-based RL, model-free RL, and how to develop basic agents. You'll discover how to implement advanced deep reinforcement learning algorithms such as actor-critic, deep deterministic policy gradients, deep-Q networks, proximal policy optimization, and deep recurrent Q-networks for training your RL agents. As you advance, you’ll explore the applications of reinforcement learning by building cryptocurrency trading agents, stock/share trading agents, and intelligent agents for automating task completion. Finally, you'll find out how to deploy deep reinforcement learning agents to the cloud and build cross-platform apps using TensorFlow 2.x.By the end of this TensorFlow book, you'll have gained a solid understanding of deep reinforcement learning algorithms and their implementations from scratch.
Palanisamy P
With deep reinforcement learning, you can build intelligent agents, products, and services that can go beyond computer vision or perception to perform actions. TensorFlow 2.x is the latest major release of the most popular deep learning framework used to develop and train deep neural networks (DNNs). This book contains easy-to-follow recipes for leveraging TensorFlow 2.x to develop artificial intelligence applications.Starting with an introduction to the fundamentals of deep reinforcement learning and TensorFlow 2.x, the book covers OpenAI Gym, model-based RL, model-free RL, and how to develop basic agents. You'll discover how to implement advanced deep reinforcement learning algorithms such as actor-critic, deep deterministic policy gradients, deep-Q networks, proximal policy optimization, and deep recurrent Q-networks for training your RL agents. As you advance, you’ll explore the applications of reinforcement learning by building cryptocurrency trading agents, stock/share trading agents, and intelligent agents for automating task completion. Finally, you'll find out how to deploy deep reinforcement learning agents to the cloud and build cross-platform apps using TensorFlow 2.x.By the end of this TensorFlow book, you'll have gained a solid understanding of deep reinforcement learning algorithms and their implementations from scratch.
Jesús Martínez
Computer vision is a scientific field that enables machines to identify and process digital images and videos. This book focuses on independent recipes to help you perform various computer vision tasks using TensorFlow.The book begins by taking you through the basics of deep learning for computer vision, along with covering TensorFlow 2.x’s key features, such as the Keras and tf.data.Dataset APIs. You’ll then learn about the ins and outs of common computer vision tasks, such as image classification, transfer learning, image enhancing and styling, and object detection. The book also covers autoencoders in domains such as inverse image search indexes and image denoising, while offering insights into various architectures used in the recipes, such as convolutional neural networks (CNNs), region-based CNNs (R-CNNs), VGGNet, and You Only Look Once (YOLO). Moving on, you’ll discover tips and tricks to solve any problems faced while building various computer vision applications. Finally, you’ll delve into more advanced topics such as Generative Adversarial Networks (GANs), video processing, and AutoML, concluding with a section focused on techniques to help you boost the performance of your networks.By the end of this TensorFlow book, you’ll be able to confidently tackle a wide range of computer vision problems using TensorFlow 2.x.
Tony Holdroyd
TensorFlow is one of the most popular machine learning frameworks in Python. With this book, you will improve your knowledge of some of the latest TensorFlow features and will be able to perform supervised and unsupervised machine learning and also train neural networks.After giving you an overview of what's new in TensorFlow 2.0 Alpha, the book moves on to setting up your machine learning environment using the TensorFlow library. You will perform popular supervised machine learning tasks using techniques such as linear regression, logistic regression, and clustering. You will get familiar with unsupervised learning for autoencoder applications. The book will also show you how to train effective neural networks using straightforward examples in a variety of different domains.By the end of the book, you will have been exposed to a large variety of machine learning and neural network TensorFlow techniques.
Abhishek Thakur, Alberto Boschetti, Luca Massaron, Alexey...
TensorFlow is one of the most popular frameworks used for machine learning and, more recently, deep learning. It provides a fast and efficient framework for training different kinds of deep learning models, with very high accuracy. This book is your guide to master deep learning with TensorFlow with the help of 10 real-world projects.TensorFlow Deep Learning Projects starts with setting up the right TensorFlow environment for deep learning. You'll learn how to train different types of deep learning models using TensorFlow, including Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, and Generative Adversarial Networks. While doing this, you will build end-to-end deep learning solutions to tackle different real-world problems in image processing, recommendation systems, stock prediction, and building chatbots, to name a few. You will also develop systems that perform machine translation and use reinforcement learning techniques to play games.By the end of this book, you will have mastered all the concepts of deep learning and their implementation with TensorFlow, and will be able to build and train your own deep learning models with TensorFlow confidently.