The Coder's Apprentice
The Coder's Apprentice is a course book, written by Pieter Spronck, that is aimed at teaching Python 3 to students and teenagers who are completely new to programming. Contrary to many of the other books that teach Python programming, this book assumes no previous knowledge of programming on the part of the students, and contains numerous exercises that allow students to train their programming skills. The goal of this book is to teach anyone how to create useful programs in Python. It should be usable by secondary school students, and university and college students for whom computer programming is not naturally incorporated in their course program. Its aim is to give anyone the means to become proficient in programming, and as such get prepared to perform well in the 21st century job market. ...
The Coder's Apprentice is a course book, written by Pieter Spronck, that is aimed at teaching Python 3 to students and teenagers who are completely new to programming. Contrary to many of the other books that teach Python programming, this book assumes no previous knowledge of programming on the part of the students, and contains numerous exercises that allow students to train their programming skills. The goal of this book is to teach anyone how to create useful programs in Python. It should be usable by secondary school students, and university and college students for whom computer programming is not naturally incorporated in their course program. Its aim is to give anyone the means to become proficient in programming, and as such get prepared to perform well in the 21st century job market. ...
Artificial Intelligence in Finance
The widespread adoption of AI and machine learning is revolutionizing many industries today. Once these technologies are combined with the programmatic availability of historical and real-time financial data, the financial industry will also change fundamentally. With this practical book, you'll learn how to use AI and machine learning to discover statistical inefficiencies in financial markets and exploit them through algorithmic trading. Author Yves Hilpisch shows practitioners, students, and academics in both finance and data science practical ways to apply machine learning and deep learning algorithms to finance. Thanks to lots of self-contained Python examples, you'll be able to replicate all results and figures presented in the book. In five parts, this guide helps you: Learn central notions and algorithms from AI, including recent breakthroughs on the way to artificial general intelligence (AGI) and superintelligence (SI); Understand why data-driven finance, AI, and machin ...
The widespread adoption of AI and machine learning is revolutionizing many industries today. Once these technologies are combined with the programmatic availability of historical and real-time financial data, the financial industry will also change fundamentally. With this practical book, you'll learn how to use AI and machine learning to discover statistical inefficiencies in financial markets and exploit them through algorithmic trading. Author Yves Hilpisch shows practitioners, students, and academics in both finance and data science practical ways to apply machine learning and deep learning algorithms to finance. Thanks to lots of self-contained Python examples, you'll be able to replicate all results and figures presented in the book. In five parts, this guide helps you: Learn central notions and algorithms from AI, including recent breakthroughs on the way to artificial general intelligence (AGI) and superintelligence (SI); Understand why data-driven finance, AI, and machin ...
Building Versatile Mobile Apps with Python and REST
Develop versatile iOS apps using Python with RESTful web services. This book will show you how to blend Django, a high-level Python Web framework, with Django REST, the powerful, feature-filled extension, to build iOS mobile apps. Using easy-to-follow examples, you'll begin by building a simple app using the RESTful Web API and iOS. You'll begin by using traditional Django to create models and connect your App to the database. You'll then see how to serialize your data and create the RESTful API. The second part of the book introduces Xcode, a programming environment to develop iOS apps. Using Swift, the programming language for iOS, you'll design the actual app. Once you have your back-end in Django and a front-end in Swift, you'll connect them using our RESTful API. You'll be able to log in, browse places of interest, and rate them and leave comments. Guided step-by-step instructions, Building Versatile Mobile Apps with Python and REST will demonstrate how easy it is to use Py ...
Develop versatile iOS apps using Python with RESTful web services. This book will show you how to blend Django, a high-level Python Web framework, with Django REST, the powerful, feature-filled extension, to build iOS mobile apps. Using easy-to-follow examples, you'll begin by building a simple app using the RESTful Web API and iOS. You'll begin by using traditional Django to create models and connect your App to the database. You'll then see how to serialize your data and create the RESTful API. The second part of the book introduces Xcode, a programming environment to develop iOS apps. Using Swift, the programming language for iOS, you'll design the actual app. Once you have your back-end in Django and a front-end in Swift, you'll connect them using our RESTful API. You'll be able to log in, browse places of interest, and rate them and leave comments. Guided step-by-step instructions, Building Versatile Mobile Apps with Python and REST will demonstrate how easy it is to use Py ...
Advanced Analytics in Power BI with R and Python
This easy-to-follow guide provides R and Python recipes to help you learn and apply the top languages in the field of data analytics to your work in Microsoft Power BI. Data analytics expert and author Ryan Wade shows you how to use R and Python to perform tasks that are extremely hard, if not impossible, to do using native Power BI tools. For example, you will learn to score Power BI data using custom data science models and powerful models from Microsoft Cognitive Services. The R and Python languages are powerful complements to Power BI. They enable advanced data transformation techniques that are difficult to perform in Power BI in its default configuration but become easier by leveraging the capabilities of R and Python. If you are a business analyst, data analyst, or a data scientist who wants to push Power BI and transform it from being just a business intelligence tool into an advanced data analytics tool, then this is the book to help you do that. ...
This easy-to-follow guide provides R and Python recipes to help you learn and apply the top languages in the field of data analytics to your work in Microsoft Power BI. Data analytics expert and author Ryan Wade shows you how to use R and Python to perform tasks that are extremely hard, if not impossible, to do using native Power BI tools. For example, you will learn to score Power BI data using custom data science models and powerful models from Microsoft Cognitive Services. The R and Python languages are powerful complements to Power BI. They enable advanced data transformation techniques that are difficult to perform in Power BI in its default configuration but become easier by leveraging the capabilities of R and Python. If you are a business analyst, data analyst, or a data scientist who wants to push Power BI and transform it from being just a business intelligence tool into an advanced data analytics tool, then this is the book to help you do that. ...
Computer Vision Using Deep Learning
Organizations spend huge resources in developing software that can perform the way a human does. Image classification, object detection and tracking, pose estimation, facial recognition, and sentiment estimation all play a major role in solving computer vision problems. This book will bring into focus these and other deep learning architectures and techniques to help you create solutions using Keras and the TensorFlow library. You'll also review mutliple neural network architectures, including LeNet, AlexNet, VGG, Inception, R-CNN, Fast R-CNN, Faster R-CNN, Mask R-CNN, YOLO, and SqueezeNet and see how they work alongside Python code via best practices, tips, tricks, shortcuts, and pitfalls. All code snippets will be broken down and discussed thoroughly so you can implement the same principles in your respective environments. Computer Vision Using Deep Learning offers a comprehensive yet succinct guide that stitches DL and CV together to automate operations, reduce human interven ...
Organizations spend huge resources in developing software that can perform the way a human does. Image classification, object detection and tracking, pose estimation, facial recognition, and sentiment estimation all play a major role in solving computer vision problems. This book will bring into focus these and other deep learning architectures and techniques to help you create solutions using Keras and the TensorFlow library. You'll also review mutliple neural network architectures, including LeNet, AlexNet, VGG, Inception, R-CNN, Fast R-CNN, Faster R-CNN, Mask R-CNN, YOLO, and SqueezeNet and see how they work alongside Python code via best practices, tips, tricks, shortcuts, and pitfalls. All code snippets will be broken down and discussed thoroughly so you can implement the same principles in your respective environments. Computer Vision Using Deep Learning offers a comprehensive yet succinct guide that stitches DL and CV together to automate operations, reduce human interven ...
Beyond the Basic Stuff with Python
You've completed a basic Python programming tutorial or finished Al Sweigart's best selling Automate the Boring Stuff with Python. What's the next step toward becoming a capable, confident software developer? Welcome to Beyond the Basic Stuff with Python. More than a mere collection of advanced syntax and masterful tips for writing clean code, you'll learn how to advance your Python programming skills by using the command line and other professional tools like code formatters, type checkers, linters, and version control. Sweigart takes you through best practices for setting up your development environment, naming variables, and improving readability, then tackles documentation, organization and performance measurement, as well as object-oriented design and the Big-O algorithm analysis commonly used in coding interviews. The skills you learn will boost your ability to program - not just in Python but in any language. You'll learn: - Coding style, and how to use Python's Black aut ...
You've completed a basic Python programming tutorial or finished Al Sweigart's best selling Automate the Boring Stuff with Python. What's the next step toward becoming a capable, confident software developer? Welcome to Beyond the Basic Stuff with Python. More than a mere collection of advanced syntax and masterful tips for writing clean code, you'll learn how to advance your Python programming skills by using the command line and other professional tools like code formatters, type checkers, linters, and version control. Sweigart takes you through best practices for setting up your development environment, naming variables, and improving readability, then tackles documentation, organization and performance measurement, as well as object-oriented design and the Big-O algorithm analysis commonly used in coding interviews. The skills you learn will boost your ability to program - not just in Python but in any language. You'll learn: - Coding style, and how to use Python's Black aut ...
Practical Deep Learning
If you've been curious about machine learning but didn't know where to start, this is the book you've been waiting for. Focusing on the subfield of machine learning known as deep learning, it explains core concepts and gives you the foundation you need to start building your own models. Rather than simply outlining recipes for using existing toolkits, Practical Deep Learning teaches you the why of deep learning and will inspire you to explore further. All you need is basic familiarity with computer programming and high school math - the book will cover the rest. After an introduction to Python, you'll move through key topics like how to build a good training dataset, work with the scikit-learn and Keras libraries, and evaluate your models' performance. You'll also learn: - How to use classic machine learning models like k-Nearest Neighbors, Random Forests, and Support Vector Machines; - How neural networks work and how they're trained; - How to use convolutional neural network ...
If you've been curious about machine learning but didn't know where to start, this is the book you've been waiting for. Focusing on the subfield of machine learning known as deep learning, it explains core concepts and gives you the foundation you need to start building your own models. Rather than simply outlining recipes for using existing toolkits, Practical Deep Learning teaches you the why of deep learning and will inspire you to explore further. All you need is basic familiarity with computer programming and high school math - the book will cover the rest. After an introduction to Python, you'll move through key topics like how to build a good training dataset, work with the scikit-learn and Keras libraries, and evaluate your models' performance. You'll also learn: - How to use classic machine learning models like k-Nearest Neighbors, Random Forests, and Support Vector Machines; - How neural networks work and how they're trained; - How to use convolutional neural network ...
A Practical Introduction to Python Programming
This book started out as about 30 pages of notes for students in my introductory programming class at Mount St. Mary's University. Most of these students have no prior programming experience, and that has affected my approach. I leave out a lot of technical details and sometimes I oversimplify things. Some of these details are filled in later in the book, though other details are never filled in. But this book is not designed to cover everything, and I recommend reading other books and the Python documentation to fill in the gaps. The style of programming in this book is geared towards the kinds of programming things I like to do - short programs, often of a mathematical nature, small utilities to make my life easier, and small computer games. In fact, the things I cover in the book are the things that I have found most useful or interesting in my programming experience, and this book serves partly to document those things for myself. This book is not designed as a thorough preparat ...
This book started out as about 30 pages of notes for students in my introductory programming class at Mount St. Mary's University. Most of these students have no prior programming experience, and that has affected my approach. I leave out a lot of technical details and sometimes I oversimplify things. Some of these details are filled in later in the book, though other details are never filled in. But this book is not designed to cover everything, and I recommend reading other books and the Python documentation to fill in the gaps. The style of programming in this book is geared towards the kinds of programming things I like to do - short programs, often of a mathematical nature, small utilities to make my life easier, and small computer games. In fact, the things I cover in the book are the things that I have found most useful or interesting in my programming experience, and this book serves partly to document those things for myself. This book is not designed as a thorough preparat ...
Advancing into Analytics
Data analytics may seem daunting, but if you're an experienced Excel user, you have a unique head start. With this hands-on guide, intermediate Excel users will gain a solid understanding of analytics and the data stack. By the time you complete this book, you'll be able to conduct exploratory data analysis and hypothesis testing using a programming language. Exploring and testing relationships are core to analytics. By using the tools and frameworks in this book, you'll be well positioned to continue learning more advanced data analysis techniques. Author George Mount, founder and CEO of Stringfest Analytics, demonstrates key statistical concepts with spreadsheets, then pivots your existing knowledge about data manipulation into R and Python programming. This practical book guides you through: - Foundations of analytics in Excel: Use Excel to test relationships between variables and build compelling demonstrations of important concepts in statistics and analytics; - From Excel ...
Data analytics may seem daunting, but if you're an experienced Excel user, you have a unique head start. With this hands-on guide, intermediate Excel users will gain a solid understanding of analytics and the data stack. By the time you complete this book, you'll be able to conduct exploratory data analysis and hypothesis testing using a programming language. Exploring and testing relationships are core to analytics. By using the tools and frameworks in this book, you'll be well positioned to continue learning more advanced data analysis techniques. Author George Mount, founder and CEO of Stringfest Analytics, demonstrates key statistical concepts with spreadsheets, then pivots your existing knowledge about data manipulation into R and Python programming. This practical book guides you through: - Foundations of analytics in Excel: Use Excel to test relationships between variables and build compelling demonstrations of important concepts in statistics and analytics; - From Excel ...
Snake Wrangling for Kids
Python for Kids is a lighthearted introduction to the Python language and to programming in general, complete with illustrations and kid-friendly examples. We begin with the basics of how to install Python and write simple commands. In bite-sized chapters, you'll discover the essentials of Python, including how to use Python's extensive standard library, the difference between strings and lists, and using for-loops and while-loops. By the end of the book, readers have built a couple of games and created drawings with Python's graphics library, Tkinter. Each chapter closes with fun and relevant exercises that challenge the reader to put their newly acquired knowledge to the test. ...
Python for Kids is a lighthearted introduction to the Python language and to programming in general, complete with illustrations and kid-friendly examples. We begin with the basics of how to install Python and write simple commands. In bite-sized chapters, you'll discover the essentials of Python, including how to use Python's extensive standard library, the difference between strings and lists, and using for-loops and while-loops. By the end of the book, readers have built a couple of games and created drawings with Python's graphics library, Tkinter. Each chapter closes with fun and relevant exercises that challenge the reader to put their newly acquired knowledge to the test. ...