Python

Build deep learning applications, such as computer vision, speech recognition, and chatbots, using frameworks such as TensorFlow and Keras. This book helps you to ramp up your practical know-how in a

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 techniqu

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

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 pract

Master the essential skills needed to recognize and solve complex problems with machine learning and deep learning. Using real-world examples that leverage the popular Python machine learning ecosyste

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 Pyt

Deploy deep learning solutions in production with ease using TensorFlow. You'll also develop the mathematical understanding and intuition required to invent new deep learning architectures and solutio

Quickly learn to program for microcontrollers and IoT devices without a lot of study and expense. MicroPython and controllers that support it eliminate the need for programming in a C-like language, m

Embrace machine learning approaches and Python to enable automatic rendering of rich insights and solve business problems. The book uses a hands-on case study-based approach to crack real-world applic

Quickly learn how to automate unit testing of Python 3 code with Python 3 automation libraries, such as doctest, unittest, nose, nose2, and pytest.This book explores the important concepts in software

Migrate from pandas and scikit-Learn to PySpark to handle vast amounts of data and achieve faster data processing time. This book will show you how to make this transition by adapting your skills and leveraging the similarities in syntax, functionality, and interoperability between these tools. Distributed Machine Learning with PySpark offers a roadmap to data scientists considering transitioning from small data libraries (pandas/scikit-learn) to big data processing and machine learning with PySpark. You will learn to translate Python code from pandas/scikit-learn to PySpark to preprocess large volumes of data and build, train, test, and evaluate popular machine learning algorithms such as linear and logistic regression, decision trees, random forests, support vector machines, Na鴳e Bayes, and neural networks. After completing this book, you will understand the foundational concepts of data preparation and machine learning and will have the skills necessary to apply these methods using

Implement real-time data processing applications on the Raspberry Pi. This book uniquely helps you work with data science concepts as part of real-time applications using the Raspberry Pi as a localized cloud. You'll start with a brief introduction to data science followed by a dedicated look at the fundamental concepts of Python programming. Here you'll install the software needed for Python programming on the Pi, and then review the various data types and modules available. The next steps are to set up your Pis for gathering real-time data and incorporate the basic operations of data science related to real-time applications. You'll then combine all these new skills to work with machine learning concepts that will enable your Raspberry Pi to learn from the data it gathers. Case studies round out the book to give you an idea of the range of domains where these concepts can be applied. By the end of Data Science with the Raspberry Pi, you'll understand that many applications are now de

Build practical applications of computer vision using the OpenCV library with Python. This book discusses different facets of computer vision such as image and object detection, tracking and motion an

Learn about bot programming, using all the latest and greatest programming languages, including Python, Go, and Clojure, so you can feel at ease writing your Telegram bot in a way that suits you.This

Learn how to get started with robotics programming using Robot Operation System (ROS). Targeted for absolute beginners in ROS, Linux, and Python, this short guide shows you how to build your own robot

Get a jump start on using Azure HDInsight and Hadoop Ecosystem components. As most Hadoop and Big Data projects are written in either Java, Scala, or Python, this book minimizes the effort to learn an

Microsoft’s Dynamic Language Runtime (DLR) is a platform for running dynamic languages such as Ruby and Python on an equal footing with compiled languages such as C#. Furthermore, the runtime is the f

Jython is an open source implementation of the high-level, dynamic, object-oriented scripting language Python seamlessly integrated with the Java platform. The predecessor to Jython, JPython, is certi

Beginning Django E-Commerce guides you through producing an e-commerce site using Django, the most popular Python web development framework. Topics covered include how to make a shopping cart, a check

Provides information on using the Python-based framework to create Web sites.

Provides information on using the Python-based framework to create Web sites.

Provides information on writing Web applications using the Python-based Web development framework, Django.

In this book, cofounder and lead developer James Gardner brings you a comprehensive introduction to Pylons, the web framework that uses the best of Ruby, Python, and Perl and the emerging WSGI standar

This succinct guide discusses regular expressions in a direct, easy manner without exhaustive syntax explanation and covers the major open source languages: Perl, PHP, grep, vim, Python, and shell. Or

Discover clean ways to write code that will run on both Python 2 and 3.This book is tutorial-oriented with detailed examples of how to convert existing Python 2-compatible code to code that will run r