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Modern Data Access with Entity Framework Core
Modern Data Access with Entity Framework Core

C# developers, here's your opportunity to learn the ins-and-outs of Entity Framework Core, Microsoft's recently redesigned object-relational mapper. Benefit from hands-on learning that will teach you how to tackle frustrating database challenges, such as workarounds to missing features in Entity Framework Core, and learn how to optimize the performance of your applications, head-on! Modern Data Access with Entity Framework Core teaches best practices, guidance, and shortcuts that will significantly reduce the amount of resources you internally dedicate to programming data access code. The proven methods and tools taught in this book, such as how to get better performance, and the ability to select the platform of your choice, will save you valuable time and allow you to create seamless data access. Dive into succinct guidance that covers the gamut - from installing Entity Framework Core, reverse engineering, forward engineering (including schema migrations), and data reading and modif ...
Deep Learning for Natural Language Processing
Deep Learning for Natural Language Processing

Discover the concepts of deep learning used for natural language processing (NLP), with full-fledged examples of neural network models such as recurrent neural networks, long short-term memory networks, and sequence-2-sequence models. You'll start by covering the mathematical prerequisites and the fundamentals of deep learning and NLP with practical examples. The first three chapters of the book cover the basics of NLP, starting with word-vector representation before moving onto advanced algorithms. The final chapters focus entirely on implementation, and deal with sophisticated architectures such as RNN, LSTM, and Seq2seq, using Python tools: TensorFlow, and Keras. Deep Learning for Natural Language Processing follows a progressive approach and combines all the knowledge you have gained to build a question-answer chatbot system. This book is a good starting point for people who want to get started in deep learning for NLP. All the code presented in the book will be available in ...
Pro Machine Learning Algorithms
Pro Machine Learning Algorithms

Bridge the gap between a high-level understanding of how an algorithm works and knowing the nuts and bolts to tune your models better. This book will give you the confidence and skills when developing all the major machine learning models. In Pro Machine Learning Algorithms, you will first develop the algorithm in Excel so that you get a practical understanding of all the levers that can be tuned in a model, before implementing the models in Python/R. You will cover all the major algorithms: supervised and unsupervised learning, which include linear/logistic regression; k-means clustering; PCA; recommender system; decision tree; random forest; GBM; and neural networks. You will also be exposed to the latest in deep learning through CNNs, RNNs, and word2vec for text mining. You will be learning not only the algorithms, but also the concepts of feature engineering to maximize the performance of a model. You will see the theory along with case studies, such as sentiment classification, ...
Hands-On Transfer Learning with Python
Hands-On Transfer Learning with Python

Transfer learning is a machine learning (ML) technique where knowledge gained during training a set of problems can be used to solve other similar problems. The purpose of this book is two-fold; firstly, we focus on detailed coverage of deep learning (DL) and transfer learning, comparing and contrasting the two with easy-to-follow concepts and examples. The second area of focus is real-world examples and research problems using TensorFlow, Keras, and the Python ecosystem with hands-on examples. The book starts with the key essential concepts of ML and DL, followed by depiction and coverage of important DL architectures such as convolutional neural networks (CNNs), deep neural networks (DNNs), recurrent neural networks (RNNs), long short-term memory (LSTM), and capsule networks. Our focus then shifts to transfer learning concepts, such as model freezing, fine-tuning, pre-trained models including VGG, inception, ResNet, and how these systems perform better than DL models with pract ...
Learn Raspberry Pi Programming with Python, 2nd Edition
Learn Raspberry Pi Programming with Python, 2nd Edition

Learn how to program your nifty new $35 computer to make a web spider, a weather station, a media server, and more. This book explores how to make a variety of fun and even useful projects, from a web bot to search and download files to a toy to drive your pets insane. Even if you're completely new to programming in general, you'll see how easy it is to create a home security system, an underwater photography system, an RC plane with a camera, and even a near-space weather balloon with a camera. You'll learn how to use Pi with Arduino as well as Pi with Gertboard, an expansion board with an onboard ATmega microcontroller. Learn Raspberry Pi Programming with Python 2nd Edition has been fully updated in this new edition to cover the features of the new boards. You'll learn how to program in Python on your Raspberry Pi with hands-on examples and fun projects. Set up your new Raspberry Pi; Build unique projects across a range of interests; Program basic functions and processes usi ...
Hands-On Convolutional Neural Networks with TensorFlow
Hands-On Convolutional Neural Networks with TensorFlow

Convolutional Neural Networks (CNN) are one of the most popular architectures used in computer vision apps. This book is an introduction to CNNs through solving real-world problems in deep learning while teaching you their implementation in popular Python library - TensorFlow. By the end of the book, you will be training CNNs in no time! We start with an overview of popular machine learning and deep learning models, and then get you set up with a TensorFlow development environment. This environment is the basis for implementing and training deep learning models in later chapters. Then, you will use Convolutional Neural Networks to work on problems such as image classification, object detection, and semantic segmentation. After that, you will use transfer learning to see how these models can solve other deep learning problems. You will also get a taste of implementing generative models such as autoencoders and generative adversarial networks. Later on, you will see useful tips ...
Modern Scala Projects
Modern Scala Projects

Scala, together with the Spark Framework, forms a rich and powerful data processing ecosystem. Modern Scala Projects is a journey into the depths of this ecosystem. The machine learning (ML) projects presented in this book enable you to create practical, robust data analytics solutions, with an emphasis on automating data workflows with the Spark ML pipeline API. This book showcases or carefully cherry-picks from Scala's functional libraries and other constructs to help readers roll out their own scalable data processing frameworks. The projects in this book enable data practitioners across all industries gain insights into data that will help organizations have strategic and competitive advantage. Modern Scala Projects focuses on the application of supervisory learning ML techniques that classify data and make predictions. You'll begin with working on a project to predict a class of flower by implementing a simple machine learning model. Next, you'll create a cancer diagnosis class ...
Beginning Java Data Structures and Algorithms
Beginning Java Data Structures and Algorithms

Learning about data structures and algorithms gives you a better insight on how to solve common programming problems. Most of the problems faced everyday by programmers have been solved, tried, and tested. By knowing how these solutions work, you can ensure that you choose the right tool when you face these problems. This book teaches you tools that you can use to build efficient applications. It starts with an introduction to algorithms and big O notation, later explains bubble, merge, quicksort, and other popular programming patterns. You'll also learn about data structures such as binary trees, hash tables, and graphs. The book progresses to advanced concepts, such as algorithm design paradigms and graph theory. By the end of the book, you will know how to correctly implement common algorithms and data structures within your applications. ...
Mastering Python Design Patterns, 2nd Edition
Mastering Python Design Patterns, 2nd Edition

Python is an object-oriented scripting language that is used in a wide range of categories. In software engineering, a design pattern is an elected solution for solving software design problems. Although they have been around for a while, design patterns remain one of the top topics in software engineering, and are a ready source for software developers to solve the problems they face on a regular basis. This book takes you through a variety of design patterns and explains them with real-world examples. You will get to grips with low-level details and concepts that show you how to write Python code, without focusing on common solutions as enabled in Java and C++. You'll also fnd sections on corrections, best practices, system architecture, and its designing aspects. This book will help you learn the core concepts of design patterns and the way they can be used to resolve software design problems. You'll focus on most of the Gang of Four (GoF) design patterns, which are used to solve ev ...
Practical Video Game Bots
Practical Video Game Bots

Develop and use bots in video gaming to automate game processes and see possible ways to avoid this kind of automation. This book explains how bots can be very helpful in games such as multiplayer online games, both for training your character and for automating repetitious game processes in order to start a competition with human opponents much faster. Some players might use bots for cheating or avoiding game rules to gain an advantage over opponents - a sophisticated form of hacking that includes some elements of artificial intelligence (AI). However, while Practical Video Game Bots considers these topics, it is not a cheater's guide. Rather, this book is an attempt to overcome the information vacuum regarding bot development in video game applications. Through the use of three case study game examples, it covers most methods and technologies that are used by bot developers, and the details of anti-cheating systems. This book provides answers and useful advice for topics such ...
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