Open Data Structures (in Java)
There are plenty of books that teach introductory data structures. Some of them are very good. Most of them cost money, and the vast majority of computer science undergraduate students will shell out at least some cash on a data structures book. Open Data Structures (in Java) - The goal of this book is to free undergraduate computer science students from having to pay for an introductory data structures book. ...
There are plenty of books that teach introductory data structures. Some of them are very good. Most of them cost money, and the vast majority of computer science undergraduate students will shell out at least some cash on a data structures book. Open Data Structures (in Java) - The goal of this book is to free undergraduate computer science students from having to pay for an introductory data structures book. ...
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 ...
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 ...
Open Data Structures (in C++)
There are plenty of books that teach introductory data structures. Some of them are very good. Most of them cost money, and the vast majority of computer science undergraduate students will shell out at least some cash on a data structures book. Open Data Structures (in C++) - The goal of this project is to free undergraduate computer science students from having to pay for an introductory data structures book. ...
There are plenty of books that teach introductory data structures. Some of them are very good. Most of them cost money, and the vast majority of computer science undergraduate students will shell out at least some cash on a data structures book. Open Data Structures (in C++) - The goal of this project is to free undergraduate computer science students from having to pay for an introductory data structures book. ...
MERN Projects for Beginners
Learn how to use the MERN stack (MongoDB, Express.js, React, and Node) to build five fully functioning web apps for dating, video sharing, messaging, and social media. While creating these web apps, you'll learn key development concepts including how to use React hooks, Redux, MongoDB, Express, Heroku, Firebase, Material UI, and Google authentication. By expanding your portfolio with the projects you create, you will be well equipped as front-end developer. You will first create a dating site with a swiping feature and chat functionality. You will then build a video sharing app with videos displaying vertically. Next, you will learn to build an awesome messaging web app. Users will be able to chat in real time, as well as log in to their account using Google authentication. You will also create a photo sharing app and social media web apps with the ability to post images with captions and log in using email and password authentication. Most MERN tutorials out there today cover ba ...
Learn how to use the MERN stack (MongoDB, Express.js, React, and Node) to build five fully functioning web apps for dating, video sharing, messaging, and social media. While creating these web apps, you'll learn key development concepts including how to use React hooks, Redux, MongoDB, Express, Heroku, Firebase, Material UI, and Google authentication. By expanding your portfolio with the projects you create, you will be well equipped as front-end developer. You will first create a dating site with a swiping feature and chat functionality. You will then build a video sharing app with videos displaying vertically. Next, you will learn to build an awesome messaging web app. Users will be able to chat in real time, as well as log in to their account using Google authentication. You will also create a photo sharing app and social media web apps with the ability to post images with captions and log in using email and password authentication. Most MERN tutorials out there today cover ba ...
Cryptography and Cryptanalysis in MATLAB
Master the essentials of cryptography and cryptanalysis and learn how to put them to practical use. Each chapter of this book starts with an introduction to the concepts on which cryptographic algorithms are based and how they are used in practice, providing fully working examples for each of the algorithms presented. Implementation sections will guide you through the entire process of writing your own applications and programs using MATLAB. Cryptography and Cryptanalysis in MATLAB will serve as your definitive go-to cryptography reference, whether you are a student, professional developer, or researcher, showing how a multitude of cryptographic challenges can be overcome using the powerful tools of MATLAB. ...
Master the essentials of cryptography and cryptanalysis and learn how to put them to practical use. Each chapter of this book starts with an introduction to the concepts on which cryptographic algorithms are based and how they are used in practice, providing fully working examples for each of the algorithms presented. Implementation sections will guide you through the entire process of writing your own applications and programs using MATLAB. Cryptography and Cryptanalysis in MATLAB will serve as your definitive go-to cryptography reference, whether you are a student, professional developer, or researcher, showing how a multitude of cryptographic challenges can be overcome using the powerful tools of MATLAB. ...
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 ...
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 ...
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 ...
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 ...
Microservices in .NET, 2nd Edition
Microservices in .NET, Second Edition is a comprehensive guide to building microservice applications using the .NET stack. After a crystal-clear introduction to the microservices architectural style, it teaches you practical microservices development skills using ASP.NET. This second edition of the bestselling original has been revised with up-to-date tools for the .NET ecosystem, and more new coverage of scoping microservices and deploying to Kubernetes. Microservice architectures connect independent components that must work together as a system. Integrating new technologies like Docker and Kubernetes with Microsoft's familiar ASP.NET framework and Azure cloud platform enables .NET developers to create and manage microservices efficiently. Microservices in .NET, Second Edition teaches you to build and deploy microservices using ASP.NET and Azure services. It lays out microservice architecture simply, and then guides you through several real-world projects, such as building an e ...
Microservices in .NET, Second Edition is a comprehensive guide to building microservice applications using the .NET stack. After a crystal-clear introduction to the microservices architectural style, it teaches you practical microservices development skills using ASP.NET. This second edition of the bestselling original has been revised with up-to-date tools for the .NET ecosystem, and more new coverage of scoping microservices and deploying to Kubernetes. Microservice architectures connect independent components that must work together as a system. Integrating new technologies like Docker and Kubernetes with Microsoft's familiar ASP.NET framework and Azure cloud platform enables .NET developers to create and manage microservices efficiently. Microservices in .NET, Second Edition teaches you to build and deploy microservices using ASP.NET and Azure services. It lays out microservice architecture simply, and then guides you through several real-world projects, such as building an e ...
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 ...
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 ...
Efficient MySQL Performance
You'll find several books on basic or advanced MySQL performance, but nothing in between. That's because explaining MySQL performance without addressing its complexity is difficult. This practical book bridges the gap by teaching software engineers mid-level MySQL knowledge beyond the fundamentals, but well shy of deep-level internals required by database administrators (DBAs). Daniel Nichter shows you how to apply the best practices and techniques that directly affect MySQL performance. You'll learn how to improve performance by analyzing query execution, indexing for common SQL clauses and table joins, optimizing data access, and understanding the most important MySQL metrics. You'll also discover how replication, transactions, row locking, and the cloud influenceMySQL performance. Understand why query response time is the North Star of MySQL performance; Learn query metrics in detail, including aggregation, reporting, and analysis; See how to index effectively for common SQL c ...
You'll find several books on basic or advanced MySQL performance, but nothing in between. That's because explaining MySQL performance without addressing its complexity is difficult. This practical book bridges the gap by teaching software engineers mid-level MySQL knowledge beyond the fundamentals, but well shy of deep-level internals required by database administrators (DBAs). Daniel Nichter shows you how to apply the best practices and techniques that directly affect MySQL performance. You'll learn how to improve performance by analyzing query execution, indexing for common SQL clauses and table joins, optimizing data access, and understanding the most important MySQL metrics. You'll also discover how replication, transactions, row locking, and the cloud influenceMySQL performance. Understand why query response time is the North Star of MySQL performance; Learn query metrics in detail, including aggregation, reporting, and analysis; See how to index effectively for common SQL c ...