Applied Data Science with Python and Jupyter
Getting started with data science doesn't have to be an uphill battle. Applied Data Science with Python and Jupyter is a step-by-step guide ideal for beginners who know a little Python and are looking for a quick, fast-paced introduction to these concepts. In this book, you'll learn every aspect of the standard data workflow process, including collecting, cleaning, investigating, visualizing, and modeling data. You'll start with the basics of Jupyter, which will be the backbone of the book. After familiarizing ourselves with its standard features, you'll look at an example of it in practice with our first analysis. In the next lesson, you dive right into predictive analytics, where multiple classification algorithms are implemented. Finally, the book ends by looking at data collection techniques. You'll see how web data can be acquired with scraping techniques and via APIs, and then briefly explore interactive visualizations. ...
After a brief history of Python and key differences between Python 2 and Python 3, you'll understand how Python has been used in applications such as YouTube and Google App Engine. As you work with the language, you'll learn about control statements, delve into controlling program flow and gradually work on more structured programs via functions.
As you settle into the Python ecosystem, you'll learn about data structures and study ways to correctly store and represent information. By working through specific examples, you'll learn how Python implements object-oriented programming (OOP) concepts of abstraction, encapsulation of data, inheritance, and polymorphism. You'll be given an overview of how imports, modules, and packages work in Python how you can handle errors to prevent apps from crashing, as well as file manipulation.
By the end of this book, you'll have built up an impressive portfolio of projects and armed yourself with ...
Big Data Processing with Apache Spark
Processing big data in real time is challenging due to scalability, information consistency, and fault-tolerance. This book teaches you how to use Spark to make your overall analytical workflow faster and more efficient. You'll explore all core concepts and tools within the Spark ecosystem, such as Spark Streaming, the Spark Streaming API, machine learning extension, and structured streaming.
You'll begin by learning data processing fundamentals using Resilient Distributed Datasets (RDDs), SQL, Datasets, and Dataframes APIs. After grasping these fundamentals, you'll move on to using Spark Streaming APIs to consume data in real time from TCP sockets, and integrate Amazon Web Services (AWS) for stream consumption.
By the end of this book, you'll not only have understood how to use machine learning extensions and structured streams but you'll also be able to apply Spark in your own upcoming big data projects. ...
Mastering Flask Web Development, 2nd Edition
Flask is a popular Python framework known for its lightweight and modular design. Mastering Flask Web Development will take you on a complete tour of the Flask environment and teach you how to build a production-ready application.
You'll begin by learning about the installation of Flask and basic concepts such as MVC and accessing a database using an ORM. You will learn how to structure your application so that it can scale to any size with the help of Flask Blueprints. You'll then learn how to use Jinja2 templates with a high level of expertise. You will also learn how to develop with SQL or NoSQL databases, and how to develop REST APIs and JWT authentication. Next, you'll move on to build role-based access security and authentication using LDAP, OAuth, OpenID, and database. Also learn how to create asynchronous tasks that can scale to any load using Celery and RabbitMQ or Redis. You will also be introduced to a wide range of Flask extensions to leverage technologies such as ...
Django 2 Web Development Cookbook, 3rd Edition
Django is a framework designed to balance rapid web development with high performance. It handles high levels of user traffic and interaction, integrates with a variety of databases, and collects and processes data in real time. This book follows a task-based approach to guide you through developing with the Django 2.1 framework, starting with setting up and configuring Docker containers and a virtual environment for your project.
In the final cha ...
Keras Deep Learning Cookbook
Keras has quickly emerged as a popular deep learning library. Written in Python it allows you to train convolutional as well as recurrent neural networks with speed and accuracy.
The Keras Deep Learning Cookbook shows you how to tackle different problems encountered while training efficient deep learning models, with the help of the popular Keras library. Starting with installing and setting up Keras, the book demonstrates how you can perform deep learning with Keras in the TensorFlow. From loading data to fitting and evaluating your model for optimal performance, you will work through a step-by-step process to tackle every possible problem faced while training deep models. You will implement convolutional and recurrent neural networks, adversarial networks, and more with the help of this handy guide. In addition to this, you will learn how to train these models for real-world image and language processing tasks.
By the end of this book, you will have a practical, hands-on ...
Python 3 Object-Oriented Programming, 3rd Edition
Object-oriented programming (OOP) is a popular design paradigm in which data and behaviors are encapsulated in such a way that they can be manipulated together. This third edition of Python 3 Object-Oriented Programming fully explains classes, data encapsulation, and exceptions with an emphasis on when you can use each principle to develop well-designed software.
Starting with a detailed analysis of object-oriented programming, you will use the Python programming language to clearly grasp key concepts from the object-oriented paradigm. You will learn how to create maintainable applications by studying higher level design patterns. The book will show you the complexities of string and file manipulation, and how Python distinguishes between binary and textual data. Not one, but two very powerful automated testing systems, unittest and pytest, will be introduced in this book. You'll get a comprehensive introduction to Python's concurrent programming ecosystem.
Hands-On Data Structures and Algorithms with Python, 2nd Edition
Data structures allow you to store and organize data efficiently. They are critical to any problem, provide a complete solution, and act like reusable code. Hands-On Data Structures and Algorithms with Python teaches you the essential Python data structures and the most common algorithms for building easy and maintainable applications.
This book helps you to understand the power of linked lists, double linked lists, and circular linked lists. You will learn to create complex data structures, such as graphs, stacks, and queues. As you make your way through the chapters, you will explore the application of binary searches and binary search trees, along with learning common techniques and structures used in tasks such as preprocessing, modeling, and transforming data. In the concluding chapters, you will get to grips with organizing your code in a manageable, consistent, and extendable way. You will also study how to bubble sort, selection sort, insertion sort, and merge ...
Launch into coding with Mission Python a space-themed guide to building a complete computer game in Python. You'll learn programming fundamentals like loops, strings, and lists as you build Escape!, an exciting game with a map to explore, items to collect, and tricky logic puzzles to solve. As you work through the book, you'll build exercises and mini-projects, like making a spacewalk simulator and creating an astronaut's safety checklist that will put your new Python skills to the test.
You'll learn how to use Pygame Zero, a free resource that lets you add graphics and sound effects to your creations, and you'll get useful game-making tips, such as how to design fun puzzles and intriguing maps. Before you know it, you'll have a working, awesome game to stump your friends with (and some nifty coding skills, too!). You can follow this book using a Raspberry Pi or a Microsoft Windows PC, and the 3D graphics and sound effects you need are provided as a download. ...
Impractical Python Projects
Impractical Python Projects picks up where the complete beginner books leave off, expanding on existing concepts and introducing new tools that you'll use every day. And to keep things interesting, each project includes a zany twist featuring historical incidents, pop culture references, and literary allusions.
You'll flex your problem-solving skills and employ Python's many useful libraries to do things like: Help James Bond crack a high-tech safe with a hill-climbing algorithm; Write haiku poems using Markov Chain Analysis; Use genetic algorithms to breed a race of gigantic rats; Crack the world's most successful military cipher using cryptanalysis; Foil corporate security with invisible electronic ink; Derive the anagram, "I am Lord Voldemort" using linguistical sieves; Plan your parents secure retirement with Monte Carlo simulation; Save the sorceress Zatanna from a stabby death using palingrams; Model the Milky Way and calculate our odds of detecting alien civilizations; ...
Machine Learning with scikit-learn Quick Start Guide
Scikit-learn is a robust machine learning library for the Python programming language. It provides a set of supervised and unsupervised learning algorithms. This book is the easiest way to learn how to deploy, optimize, and evaluate all of the important machine learning algorithms that scikit-learn provides.
This book teaches you how to use scikit-learn for machine learning. You will start by setting up and configuring your machine learning environment with scikit-learn. To put scikit-learn to use, you will learn how to implement various supervised and unsupervised machine learning models. You will learn classification, regression, and clustering techniques to work with different types of datasets and train your models.
Finally, you will learn about an effective pipeline to help you build a machine learning project from scratch. By the end of this book, you will be confident in building your own machine learning models for accurate predictions. ...