||Machine Learning with Python Cookbook|
This practical guide provides nearly 200 self-contained recipes to help you solve machine learning challenges you may encounter in your daily work. If you're comfortable with Python and its libraries, including pandas and scikit-learn, you'll be able to address specific problems such as loading data, handling text or numerical data, model selection, and dimensionality reduction and many other topics.
Each recipe includes code that you can copy and paste into a toy dataset to ensure that it actually works. From there, you can insert, combine, or adapt the code to help construct your application. Recipes also include a discussion that explains the solution and provides meaningful context. This cookbook takes you beyond theory and concepts by providing the nuts and bolts you need to construct working machine learning applications.
Vectors, matrices, and arrays; Handling numerical and categorical data, text, images, and dates and times; Dimensionality reduction using feature e ...
||Flask Web Development, 2nd Edition|
Take full creative control of your web applications with Flask, the Python-based microframework. With the second edition of this hands-on book, you'll learn Flask from the ground up by developing a complete, real-world application created by author Miguel Grinberg. This refreshed edition accounts for important technology changes that have occurred in the past three years.
Explore the framework's core functionality, and learn how to extend applications with advanced web techniques such as database migrations and an application programming interface. The first part of each chapter provides you with reference and background for the topic in question, while the second part guides you through a hands-on implementation.
If you have Python experience, you're ready to take advantage of the creative freedom Flask provides. Three sections include: A thorough introduction to Flask: explore web application development basics with Flask and an application structure appropriate for medi ...
||Deep Learning with TensorFlow, 2nd Edition|
Deep learning is a branch of machine learning algorithms based on learning multiple levels of abstraction. Neural networks, which are at the core of deep learning, are being used in predictive analytics, computer vision, natural language processing, time series forecasting, and to perform a myriad of other complex tasks.
This book is conceived for developers, data analysts, machine learning practitioners and deep learning enthusiasts who want to build powerful, robust, and accurate predictive models with the power of TensorFlow v1.7, combined with other open source Python libraries.
Throughout the book, you'll learn how to develop deep learning applications for machine learning systems using Feedforward Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Autoencoders, and Factorization Machines. Discover how to attain deep learning programming on GPU in a distributed way.
You'll come away with an in-depth knowledge of machine learning techniques a ...
||Advanced Data Analytics Using Python|
Gain a broad foundation of advanced data analytics concepts and discover the recent revolution in databases such as Neo4j, Elasticsearch, and MongoDB. This book discusses how to implement ETL techniques including topical crawling, which is applied in domains such as high-frequency algorithmic trading and goal-oriented dialog systems. You'll also see examples of machine learning concepts such as semi-supervised learning, deep learning, and NLP. Advanced Data Analytics Using Python also covers important traditional data analysis techniques such as time series and principal component analysis.
After reading this book you will have experience of every technical aspect of an analytics project. You'll get to know the concepts using Python code, giving you samples to use in your own projects.
Work with data analysis techniques such as classification, clustering, regression, and forecasting; Handle structured and unstructured data, ETL techniques, and different kinds of da ...
Get Programming: Learn to code with Python introduces you to the world of writing computer programs without drowning you in confusing jargon or theory that make getting started harder than it should be. Filled with practical examples and step-by-step lessons using the easy-on-the-brain Python language, this book will get you programming in no time!
Let's face it. The only way to learn computer programming is to do it. Whether you want to skill up for your next job interview or just get a few pet projects done, programming can be an amazing tool. This book is designed especially for beginners, helping them learn to program hands on, step by step, project by project. It's time to get programming!
Get Programming: Learn to code with Python teaches you the basics of computer programming using the Python language. In this exercise-driven book, you'll be doing something on nearly every page as you work through 38 compact lessons and 7 engaging capstone proje ...
||Make Your Own Python Text Adventure|
Learn programming with Python by creating a text adventure. This book will teach you the fundamentals of programming, how to organize code, and some coding best practices. By the end of the book, you will have a working game that you can play or show off to friends. You will also be able to change the game and make it your own by writing a different story line, including new items, creating new characters, and more.
Make your own Python Text Adventure offers a structured approach to learning Python that teaches the fundamentals of the language, while also guiding the development of the customizable game. The first half of the book introduces programming concepts and Python syntax by building the basic structure of the game. You'll also apply the new concepts in homework questions (with solutions if you get stuck!) that follow each chapter. The second half of the book will shift the focus to adding features to your game and making it more entertaining for ...
||Good Habits for Great Coding|
Improve your coding skills and learn how to write readable code. Rather than teach basic programming, this book presumes that readers understand the fundamentals, and offers time-honed best practices for style, design, documenting, testing, refactoring, and more.
Taking an informal, conversational tone, author Michael Stueben offers programming stories, anecdotes, observations, advice, tricks, examples, and challenges based on his 38 years experience writing code and teaching programming classes. Trying to teach style to beginners is notoriously difficult and can easily appear pedantic. Instead, this book offers solutions and many examples to back up his ideas.
Good Habits for Great Coding distills Stueben's three decades of analyzing his own mistakes, analyzing student mistakes, searching for problems that teach lessons, and searching for simple examples to illustrate complex ideas. Having found that most learn by trying out challenging problems, and reflecting on them, each c ...
||Practical Python AI Projects|
Discover the art and science of solving artificial intelligence problems with Python using optimization modeling. This book covers the practical creation and analysis of mathematical algebraic models such as linear continuous models, non-obviously linear continuous models, and pure linear integer models. Rather than focus on theory, Practical Python AI Projects, the product of the author's decades of industry teaching and consulting, stresses the model creation aspect; contrasting alternate approaches and practical variations.
Each model is explained thoroughly and written to be executed. The source code from all examples in the book is available, written in Python using Google OR-Tools. It also includes a random problem generator, useful for industry application or study.
Build basic Python-based artificial intelligence (AI) applications; Work with mathematical optimization methods and the Google OR-Tools (Optimization Tools) suite; Create several types of p ...
||Learn Data Analysis with Python|
Get started using Python in data analysis with this compact practical guide. This book includes three exercises and a case study on getting data in and out of Python code in the right format. Learn Data Analysis with Python also helps you discover meaning in the data using analysis and shows you how to visualize it.
Each lesson is, as much as possible, self-contained to allow you to dip in and out of the examples as your needs dictate. If you are already using Python for data analysis, you will find a number of things that you wish you knew how to do in Python. You can then take these techniques and apply them directly to your own projects.
If you aren't using Python for data analysis, this book takes you through the basics at the beginning to give you a solid foundation in the topic. As you work your way through the book you will have a better of idea of how to use Python for data analysis when you are finished. ...
Quickly discover solutions to common problems, learn best practices, and understand everything wxPython has to offer. This book is for anyone wanting to learn more about how to use the wxPython desktop GUI toolkit. It assumes some prior knowledge of Python and a general understanding of wxPython or GUI development, and contains more than 50 recipes covering various tasks and aspects of the toolkit.
wxPython Recipes guides you step by step. The book takes you through how to create user interfaces in Python including adding widgets, changing background images, manipulating dialogs, managing data, and much more. Examples target both Python 2.x and 3.x, and cover both wxPython 3.0 and Phoenix, offering a complete collection of ideas to improve your GUI development. ...
||Introduction to Python for Engineers and Scientists|
Familiarize yourself with the basics of Python for engineering and scientific computations using this concise, practical tutorial that is focused on writing code to learn concepts. Introduction to Python is useful for industry engineers, researchers, and students who are looking for open-source solutions for numerical computation.
In this book you will learn by doing, avoiding technical jargon, which makes the concepts easy to learn. First you'll see how to run basic calculations, absorbing technical complexities incrementally as you progress toward advanced topics. Throughout, the language is kept simple to ensure that readers at all levels can grasp the concepts.
Understand the fundamentals of the Python programming language; Apply Python to numerical computational programming projects in engineering and science; Discover the Pythonic way of life; Apply data types, operators, and arrays; Carry out plotting for visualization; Work with functions and l ...