Mastering Predictive Analytics with scikit-learn and TensorFlowPython is a programming language that provides a wide range of features that can be used in the field of data science. Mastering Predictive Analytics with scikit-learn and TensorFlow covers various implementations of ensemble methods, how they are used with real-world datasets, and how they improve prediction accuracy in classification and regression problems.
This book starts with ensemble methods and their features. You will see that scikit-learn provides tools for choosing hyperparameters for models. As you make your way through the book, you will cover the nitty-gritty of predictive analytics and explore its features and characteristics. You will also be introduced to artificial neural networks and TensorFlow, and how it is used to create neural networks. In the final chapter, you will explore factors such as computational power, along with improvement methods and software enhancements for efficient predictive analytics.
By the end of this book, you will be well-versed in usi ...
Hands-On Neural Network Programming with C#Neural networks have made a surprise comeback in the last few years and have brought tremendous innovation in the world of artificial intelligence.
The goal of this book is to provide C# programmers with practical guidance in solving complex computational challenges using neural networks and C# libraries such as CNTK, and TensorFlowSharp. This book will take you on a step-by-step practical journey, covering everything from the mathematical and theoretical aspects of neural networks, to building your own deep neural networks into your applications with the C# and .NET frameworks.
This book begins by giving you a quick refresher of neural networks. You will learn how to build a neural network from scratch using packages such as Encog, Aforge, and Accord. You will learn about various concepts and techniques, such as deep networks, perceptrons, optimization algorithms, convolutional networks, and autoencoders. You will learn ways to add intelligent features to your .NET apps, such as ...
Python InterviewsHear from these key Python thinkers about the current status of Python, and where it's heading in the future; Listen to their close thoughts on significant Python topics, such as Python's role in scientific computing, and machine learning; Understand the direction of Python, and what needs to change for Python 4.
Each of these twenty Python Interviews can inspire and refresh your relationship with Python and the people who make Python what it is today. Let these interviews spark your own creativity, and discover how you also have the ability to make your mark on a thriving tech community. This book invites you to immerse in the Python landscape, and let these remarkable programmers show you how you too can connect and share with Python programmers around the world. Learn from their opinions, enjoy their stories, and use their tech tips.
Brett Cannon - former director of the PSF, Python core developer, led the migration to Python 3.
Steve Holden - tireless Python promoter and for ...
Security with GoGo is becoming more and more popular as a language for security experts. Its wide use in server and cloud environments, its speed and ease of use, and its evident capabilities for data analysis, have made it a prime choice for developers who need to think about security.
Security with Go is the first Golang security book, and it is useful for both blue team and red team applications. With this book, you will learn how to write secure software, monitor your systems, secure your data, attack systems, and extract information.
Defensive topics include cryptography, forensics, packet capturing, and building secure web applications.
Offensive topics include brute force, port scanning, packet injection, web scraping, social engineering, and post exploitation techniques. ...
Distributed Computing with GoDistributed Computing with Go gives developers with a good idea how basic Go development works the tools to fulfill the true potential of Golang development in a world of concurrent web and cloud applications. Nikhil starts out by setting up a professional Go development environment. Then you'll learn the basic concepts and practices of Golang concurrent and parallel development.
You'll find out in the new few chapters how to balance resources and data with REST and standard web approaches while keeping concurrency in mind. Most Go applications these days will run in a data center or on the cloud, which is a condition upon which the next chapter depends. There, you'll expand your skills considerably by writing a distributed document indexing system during the next two chapters. This system has to balance a large corpus of documents with considerable analytical demands.
Another use case is the way in which a web application written in Go can be consciously redesigned to take dist ...
Deep Reinforcement Learning Hands-OnRecent developments in reinforcement learning (RL), combined with deep learning (DL), have seen unprecedented progress made towards training agents to solve complex problems in a human-like way. Google's use of algorithms to play and defeat the well-known Atari arcade games has propelled the field to prominence, and researchers are generating new ideas at a rapid pace.
Deep Reinforcement Learning Hands-On is a comprehensive guide to the very latest DL tools and their limitations. You will evaluate methods including Cross-entropy and policy gradients, before applying them to real-world environments. Take on both the Atari set of virtual games and family favorites such as Connect4. The book provides an introduction to the basics of RL, giving you the know-how to code intelligent learning agents to take on a formidable array of practical tasks. Discover how to implement Q-learning on grid world environments, teach your agent to buy and trade stocks, and find out how natural language mo ...
Natural Language Processing with TensorFlowNatural language processing (NLP) supplies the majority of data available to deep learning applications, while TensorFlow is the most important deep learning framework currently available. Natural Language Processing with TensorFlow brings TensorFlow and NLP together to give you invaluable tools to work with the immense volume of unstructured data in today's data streams, and apply these tools to specific NLP tasks.
Thushan Ganegedara starts by giving you a grounding in NLP and TensorFlow basics. You'll then learn how to use Word2vec, including advanced extensions, to create word embeddings that turn sequences of words into vectors accessible to deep learning algorithms. Chapters on classical deep learning algorithms, like convolutional neural networks (CNN) and recurrent neural networks (RNN), demonstrate important NLP tasks as sentence classification and language generation. You will learn how to apply high-performance RNN models, like long short-term memory (LSTM) cells, to NLP t ...
Python Data Analytics, 2nd EditionExplore the latest Python tools and techniques to help you tackle the world of data acquisition and analysis. You'll review scientific computing with NumPy, visualization with matplotlib, and machine learning with scikit-learn.
This revision is fully updated with new content on social media data analysis, image analysis with OpenCV, and deep learning libraries. Each chapter includes multiple examples demonstrating how to work with each library. At its heart lies the coverage of pandas, for high-performance, easy-to-use data structures and tools for data manipulation.
Author Fabio Nelli expertly demonstrates using Python for data processing, management, and information retrieval. Later chapters apply what you've learned to handwriting recognition and extending graphical capabilities with the JavaScript D3 library. Whether you are dealing with sales data, investment data, medical data, web page usage, or other data sets, Python Data Analytics, Second Edition is an invaluable refere ...
Website Scraping with PythonClosely examine website scraping and data processing: the technique of extracting data from websites in a format suitable for further analysis. You'll review which tools to use, and compare their features and efficiency. Focusing on BeautifulSoup4 and Scrapy, this concise, focused book highlights common problems and suggests solutions that readers can implement on their own.
Website Scraping with Python starts by introducing and installing the scraping tools and explaining the features of the full application that readers will build throughout the book. You'll see how to use BeautifulSoup4 and Scrapy individually or together to achieve the desired results. Because many sites use JavaScript, you'll also employ Selenium with a browser emulator to render these sites and make them ready for scraping.
By the end of this book, you'll have a complete scraping application to use and rewrite to suit your needs. As a bonus, the author shows you options of how to deploy your spiders into th ...
Learn to Program with Python 3Move from zero knowledge of programming to comfortably writing small to medium-sized programs in Python. Fully updated for Python 3, with code and examples throughout, the book explains Python coding with an accessible, step-by-step approach designed to bring you comfortably into the world of software development.
Real-world analogies make the material understandable, with a wide variety of well-documented examples to illustrate each concept. Along the way, you'll develop short programs through a series of coding challenges that reinforce the content of the chapters.
Learn to Program with Python 3 guides you with material developed in the author's university computer science courses. The author's conversational style feels like you're working with a personal tutor. All material is thoughtfully laid out, each lesson building on previous ones.
Understand programming basics with Python, based on material developed in the author's college courses; Learn core concepts: variables, ...