IT eBooks
Download, Read, Use
Financial Theory with Python
Financial Theory with Python

Nowadays, finance, mathematics, and programming are intrinsically linked. This book provides the relevant foundations of each discipline to give you the major tools you need to get started in the world of computational finance. Using an approach where mathematical concepts provide the common background against which financial ideas and programming techniques are learned, this practical guide teaches you the basics of financial economics. Written by the best-selling author of Python for Finance, Yves Hilpisch, Financial Theory with Python explains financial, mathematical, and Python programming concepts in an integrative manner so that the interdisciplinary concepts reinforce each other. Draw upon mathematics to learn the foundations of financial theory and Python programming; Learn about financial theory, financial data modeling, and the use of Python for computational finance; Leverage simple economic models to better understand basic notions of finance and Python programming co ...
Practical Weak Supervision
Practical Weak Supervision

Most data scientists and engineers today rely on quality labeled data to train machine learning models. But building a training set manually is time-consuming and expensive, leaving many companies with unfinished ML projects. There's a more practical approach. In this book, Wee Hyong Tok, Amit Bahree, and Senja Filipi show you how to create products using weakly supervised learning models. You'll learn how to build natural language processing and computer vision projects using weakly labeled datasets from Snorkel, a spin-off from the Stanford AI Lab. Because so many companies have pursued ML projects that never go beyond their labs, this book also provides a guide on how to ship the deep learning models you build. Get up to speed on the field of weak supervision, including ways to use it as part of the data science process; Use Snorkel AI for weak supervision and data programming; Get code examples for using Snorkel to label text and image datasets; Use a weakly labeled dataset f ...
iOS 15 Programming Fundamentals with Swift
iOS 15 Programming Fundamentals with Swift

Move into iOS development by getting a firm grasp of its fundamentals, including the Xcode 13 IDE, Cocoa Touch, and the latest version of Apple's acclaimed programming language, Swift 5.5. With this thoroughly updated guide, you'll learn the Swift language, understand Apple's Xcode development tools, and discover the Cocoa framework. Explore Swift's object-oriented concepts; Become familiar with built-in Swift types; Dive deep into Swift objects, protocols, and generics; Tour the life cycle of an Xcode project; Learn how nibs are loaded; Understand Cocoa's event-driven design; Communicate with C and Objective-C. In this edition, catch up on the latest iOS programming features: Structured concurrency: async/await, tasks, and actors; Swift native formatters and attributed strings; Lazy locals and throwing getters; Enhanced collections with the Swift Algorithms and Collections packages; Xcode tweaks: column breakpoints, package collections, and Info.plist build settings; Improvement ...
Hands-on Azure Functions with C#
Hands-on Azure Functions with C#

Build serverless solutions using Azure Functions. This book provides you with a deep understanding of Azure Functions so you can build highly scalable and reliable serverless applications. The book starts with an introduction to Azure Functions and demonstrates triggers and bindings with use cases. The process to build an OTP mailer with Queue Storage Trigger and SendGrid output binding is presented, and timer triggers and blob storage binding are covered. Creating custom binding for Azure Functions and building a serverless API using Azure Functions and Azure SQL are discussed. You will know how to build a serverless API using Azure Functions and Azure Cosmos DB, and you will go over enabling application insights and Azure Monitor. Storing function secrets in Azure Key Vault is discussed as well as authentication and authorization using Azure Active Directory. You will learn how to secure your serverless apps using API Management and deploy your Azure Functions using IDEs. Deplo ...
Spring Boot with React and AWS
Spring Boot with React and AWS

Create and deploy full-stack Spring Boot applications with React and AWS. This practical and authoritative guide teaches you the fundamentals of Amazon Web Services with no prior experience. You will start by learning the fundamentals of AWS, including EC2, S3, IAM, and load balancer. Next, you will learn to deploy a Spring Boot REST API to AWS with Elastic Beanstalk, which will give you the ability to build and deploy a Spring Boot application. You will explore the RDS relational database and create an instance of a MySQL database in AWS with RDS. You will then deploy a Spring Boot application to MySQL in AWS and deploy a full-stack Spring Boot React application to AWS using Elastic Beanstalk and S3. Lastly, you will be introduced to ELB, CloudWatch, and Route 53. By the end of this book you will understand full-stack Spring Boot React applications and their deployment. If you prefer "learning by coding" then Spring Boot with React and AWS is the book for you. ...
Pro Java Microservices with Quarkus and Kubernetes
Pro Java Microservices with Quarkus and Kubernetes

Build and design microservices using Java and the Red Hat Quarkus Framework. This book will help you quickly get started with the features and concerns of a microservices architecture. It will introduce Docker and Kubernetes to help you deploy your microservices. You will be guided on how to install the appropriate tools to work properly. For those who are new to enterprise development using Quarkus, you will be introduced to its core principles and main features through a deep step-by-step tutorial. For experts, this book offers some recipes that illustrate how to split monoliths and implement microservices and deploy them as containers to Kubernetes. By the end of reading this book, you will have practical hands-on experience of building microservices using Quarkus and you will master deploying them to Kubernetes. ...
First Semester in Numerical Analysis with Python
First Semester in Numerical Analysis with Python

The book is based on "First semester in Numerical Analysis with Julia". The contents of the original book are retained, while all the algorithms are implemented in Python (Version 3.8.0). Python is an open source (under OSI), interpreted, general-purpose programming language that has a large number of users around the world. Python is ranked the third in August 2020 by the TIOBE programming community index 2 , a measure of popularity of programming languages, and is the top-ranked interpreted language. We hope this book will better serve readers who are interested in a first course in Numerical Analysis, but are more familiar with Python for the implementation of the algorithms. The first chapter of the book has a self-contained tutorial for Python, including how to set up the computer environment. Anaconda, the open-source individual edition, is recommended for an easy installation of Python and effortless management of Python packages, and the Jupyter environment, a web-based inte ...
Pipeline as Code
Pipeline as Code

Pipeline as Code is a practical guide to automating your development pipeline in a cloud-native, service-driven world. You'll use the latest infrastructure-as-code tools like Packer and Terraform to develop reliable CI/CD pipelines for numerous cloud-native applications. Follow this book's insightful best practices, and you'll soon be delivering software that's quicker to market, faster to deploy, and with less last-minute production bugs. Treat your CI/CD pipeline like the real application it is. With the Pipeline as Code approach, you create a collection of scripts that replace the tedious web UI wrapped around most CI/CD systems. Code-driven pipelines are easy to use, modify, and maintain, and your entire CI pipeline becomes more efficient because you directly interact with core components like Jenkins, Terraform, and Docker. In Pipeline as Code you'll learn to build reliable CI/CD pipelines for cloud-native applications. With Jenkins as the backbone, you'll programmatically c ...
Pandas in Action
Pandas in Action

Pandas has rapidly become one of Python's most popular data analysis libraries. In Pandas in Action, a friendly and example-rich introduction, author Boris Paskhaver shows you how to master this versatile tool and take the next steps in your data science career. You'll learn how easy Pandas makes it to efficiently sort, analyze, filter and munge almost any type of data. Data analysis with Python doesn't have to be hard. If you can use a spreadsheet, you can learn pandas! While its grid-style layouts may remind you of Excel, pandas is far more flexible and powerful. This Python library quickly performs operations on millions of rows, and it interfaces easily with other tools in the Python data ecosystem. It's a perfect way to up your data game. Pandas in Action introduces Python-based data analysis using the amazing pandas library. You'll learn to automate repetitive operations and gain deeper insights into your data that would be impractical - or impossible - in Excel. Each chapt ...
Deep Learning with Python, 2nd Edition
Deep Learning with Python, 2nd Edition

Deep Learning with Python has taught thousands of readers how to put the full capabilities of deep learning into action. This extensively revised second edition introduces deep learning using Python and Keras, and is loaded with insights for both novice and experienced ML practitioners. You'll learn practical techniques that are easy to apply in the real world, and important theory for perfecting neural networks. Recent innovations in deep learning unlock exciting new software capabilities like automated language translation, image recognition, and more. Deep learning is quickly becoming essential knowledge for every software developer, and modern tools like Keras and TensorFlow put it within your reach - even if you have no background in mathematics or data science. This book shows you how to get started. Deep Learning with Python, Second Edition introduces the field of deep learning using Python and the powerful Keras library. In this revised and expanded new edition, Keras cre ...
← Prev       Next →
Reproduction of site books is authorized only for informative purposes and strictly for personal, private use.
Only Direct Download
IT eBooks Group © 2011-2026