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R 1,547.63
Introduction to Machine Learning with Python
Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination. You'll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Muller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book.With this book, you'll learn: Fundamental concepts and applications of machine learning Advantages and shortcomings of widely used machine learning algorithms How to represent data processed by machine learning, including which data aspects to focus on Advanced methods for model evaluation and parameter tuning The concept of pipelines for chaining models and encapsulating your workflow Methods for working with text data, including text-specific processing techniques Suggestions for improving your machine learning and data science skills
R 2,076.00
Hands-on JavaScript for Python Developers
Build robust full-stack web applications using two of the world’s most popular programming languages Python and JavaScriptKey FeaturesDiscover similarities and differences between JavaScript and Python coding conventionsExplore frontend web concepts, UI/UX techniques, and JavaScript frameworks to enhance your web development skillsPut your JS knowledge into practice by developing a full-stack web app with React and ExpressBook DescriptionKnowledge of Python is a great foundation for learning other languages. This book will help you advance in your software engineering career by leveraging your Python programming skills to learn JavaScript and apply its unique features not only for frontend web development but also for streamlining work on the backend.Starting with the basics of JavaScript, you’ll cover its syntax, its use in the browser, and its frameworks and libraries. From working with user interactions and ingesting data from APIs through to creating APIs with Node.js, this book will help you get up and running with JavaScript using hands-on exercises, code snippets, and detailed descriptions of JavaScript implementation and benefits. To understand the use of JavaScript in the backend, you’ll explore Node.js and discover how it communicates with databases. As you advance, you’ll get to grips with creating your own RESTful APIs and connecting the frontend and backend for holistic full-stack development knowledge.By the end of this Python JavaScript book, you’ll have the knowledge you need to write full-fledged web applications from start to finish. You’ll have also gained hands-on experience of working through several projects, which will help you advance in your career as a JavaScript developer.What you will learnDiscover the differences between Python and JavaScript at both the syntactical and semantical levelBecome well versed in implementing JavaScript in the frontend as well as the backendUnderstand the separation of concerns while using Python programming for server-side developmentGet to grips with frontend web development tasks, including UI/UX design, form validation, animations, and much moreCreate modern interaction interfaces for your Python web applicationExplore modern web technologies and libraries for building full-stack applicationsWho this book is forThis book is for experienced Python programmers who are looking to expand their knowledge of frontend and backend web development with JavaScript. An understanding of data types, functions, and scope is necessary to get to grips with the concepts covered in the book. Familiarity with HTML and CSS, Document Object Model (DOM), and Flask or Django will help you to learn JavaScript easily.
R 1,075.00
Python and HDF5
Gain hands-on experience with HDF5 for storing scientific data in Python. This practical guide quickly gets you up to speed on the details, best practices, and pitfalls of using HDF5 to archive and share numerical datasets ranging in size from gigabytes to terabytes. Through real-world examples and practical exercises, you'll explore topics such as scientific datasets, hierarchically organized groups, user-defined metadata, and interoperable files. Examples are applicable for users of both Python 2 and Python 3. If you're familiar with the basics of Python data analysis, this is an ideal introduction to HDF5. Get set up with HDF5 tools and create your first HDF5 file Work with datasets by learning the HDF5 Dataset object Understand advanced features like dataset chunking and compression Learn how to work with HDF5's hierarchical structure, using groups Create self-describing files by adding metadata with HDF5 attributes Take advantage of HDF5's type system to create interoperable files Express relationships among data with references, named types, and dimension scales Discover how Python mechanisms for writing parallel code interact with HDF5
R 1,038.00
R 305.00
Python Forensics
Python Forensics provides many never-before-published proven forensic modules, libraries, and solutions that can be used right out of the box. In addition, detailed instruction and documentation provided with the code samples will allow even novice Python programmers to add their own unique twists or use the models presented to build new solutions. Rapid development of new cybercrime investigation tools is an essential ingredient in virtually every case and environment. Whether you are performing post-mortem investigation, executing live triage, extracting evidence from mobile devices or cloud services, or you are collecting and processing evidence from a network, Python forensic implementations can fill in the gaps. Drawing upon years of practical experience and using numerous examples and illustrative code samples, author Chet Hosmer discusses how to: Develop new forensic solutions independent of large vendor software release schedules Participate in an open-source workbench that facilitates direct involvement in the design and implementation of new methods that augment or replace existing tools Advance your career by creating new solutions along with the construction of cutting-edge automation solutions to solve old problems
R 2,059.00
Cython
Build software that combines Python's expressivity with the performance and control of C (and C++). It's possible with Cython, the compiler and hybrid programming language used by foundational packages such as NumPy, and prominent in projects including Pandas, h5py, and scikits-learn. In this practical guide, you'll learn how to use Cython to improve Python's performance - up to 3000x - and to wrap C and C++ libraries in Python with ease. Author Kurt Smith takes you through Cython's capabilities, with sample code and in-depth practice exercises. If you're just starting with Cython, or want to go deeper, you'll learn how this language is an essential part of any performance-oriented Python programmer's arsenal.Use Cython's static typing to speed up Python code Gain hands-on experience using Cython features to boost your numeric-heavy Python Create new types with Cython - and see how fast object-oriented programming in Python can be Effectively organize Cython code into separate modules and packages without sacrificing performance Use Cython to give Pythonic interfaces to C and C++ libraries Optimize code with Cython's runtime and compile-time profiling tools Use Cython's prange function to parallelize loops transparently with OpenMP
R 1,038.00
MongoDB and Python
"MongoDB and Python" is a cookbook-style text to help Python programmers work with MongoDB. It is full of useful, practical recipes for solving real-world problems ranging from how to do fast geo queries for location-based apps to efficiently indexing your user documents for social-graph lookups to how best to integrate MongoDB with the Pyramid Web framework.
R 692.00
Programming Google App Engine with Python
This practical guide shows intermediate and advanced web and mobile app developers how to build highly scalable Python applications in the cloud with Google App Engine. The flagship of Google's Cloud Platform, App Engine hosts your app on infrastructure that grows automatically with your traffic, minimizing up-front costs and accommodating unexpected visitors. You'll learn hands-on how to perform common development tasks with App Engine services and development tools, including deployment and maintenance. App Engine's Python support includes a fast Python 2.7 interpreter, the standard library, and a WSGI-based runtime environment. Choose from many popular web application frameworks, including Django and Flask.Get a hands-on introduction to App Engine's tools and features, using an example application Simulate App Engine on your development machine with tools from Google Cloud SDK Structure your app into individually addressable modules, each with its own scaling configuration Exploit the power of the scalable Cloud Datastore, using queries, transactions, and data modeling with the ndb library Use Cloud SQL for standard relational databases with App Engine applications Learn how to deploy, manage, and inspect your application on Google infrastructure
R 1,557.00
Modern Python Standard Library Cookbook
Build optimized applications in Python by smartly implementing the standard libraryKey FeaturesStrategic recipes for effective application development in PythonTechniques to create GUIs and implement security through cryptographyBest practices for developing readily scalable, production-ready applicationsBook DescriptionThe Python 3 Standard Library is a vast array of modules that you can use for developing various kinds of applications. It contains an exhaustive list of libraries, and this book will help you choose the best one to address specific programming problems in Python.The Modern Python Standard Library Cookbook begins with recipes on containers and data structures and guides you in performing effective text management in Python. You will find Python recipes for command-line operations, networking, filesystems and directories, and concurrent execution. You will learn about Python security essentials in Python and get to grips with various development tools for debugging, benchmarking, inspection, error reporting, and tracing. The book includes recipes to help you create graphical user interfaces for your application. You will learn to work with multimedia components and perform mathematical operations on date and time. The recipes will also show you how to deploy different searching and sorting algorithms on your data.By the end of the book, you will have acquired the skills needed to write clean code in Python and develop applications that meet your needs.What you will learnStore multiple values per key in associative containersCreate interactive character-based user interfacesWork with native time and display data for your time zoneRead/write SGML family languages, both as a SAX and DOM parser to meet file sizes and other requirementsGroup equivalent items using itertools and sorted features togetherUse partials to create unary functions out of multi-argument functionsImplement hashing algorithms to store passwords in a safe wayWho this book is forIf you are a developer who wants to write highly responsive, manageable, scalable, and resilient code in Python, this book is for you. Prior programming knowledge in Python will help you make the most out of the book.
R 1,889.00
Python and AWS Cookbook
If you intend to use Amazon Web Services (AWS) for remote computing and storage, Python is an ideal programming language for developing applications and controlling your cloud-based infrastructure. This cookbook gets you started with more than two dozen recipes for using Python with AWS, based on the author's boto library. You'll find detailed recipes for working with the S3 storage service as well as EC2, the service that lets you design and build cloud applications. Each recipe includes a code solution you can use immediately, along with a discussion of why and how the recipe works. You also get detailed advice for using boto with AWS and other cloud services. This book's recipes include methods to help you: Launch instances on EC2, and keep track of them with tags Associate an Elastic IP address with an instance Restore a failed Elastic Block Store volume from a snapshot Store and monitor your own custom metrics in CloudWatch Create a bucket in S3 to contain your data objects Reduce the cost of storing noncritical data Prevent accidental deletion of data in S3
R 900.00
Python Data Visualization Cookbook
This book is written in a Cookbook style targeted towards an advanced audience. It covers the advanced topics of data visualization in Python. Python Data Visualization Cookbook is for developers that already know about Python programming in general. If you have heard about data visualization but you don't know where to start, then this book will guide you from the start and help you understand data, data formats, data visualization, and how to use Python to visualize data.You will need to know some general programming concepts, and any kind of programming experience will be helpful, but the code in this book is explained almost line by line. You don't need maths for this book, every concept that is introduced is thoroughly explained in plain English, and references are available for further interest in the topic.
R 1,498.00
R 939.84
Data Science Projects with Python
Gain hands-on experience with industry-standard data analysis and machine learning tools in PythonKey FeaturesTackle data science problems by identifying the problem to be solvedIllustrate patterns in data using appropriate visualizationsImplement suitable machine learning algorithms to gain insights from dataBook DescriptionData Science Projects with Python is designed to give you practical guidance on industry-standard data analysis and machine learning tools, by applying them to realistic data problems. You will learn how to use pandas and Matplotlib to critically examine datasets with summary statistics and graphs, and extract the insights you seek to derive. You will build your knowledge as you prepare data using the scikit-learn package and feed it to machine learning algorithms such as regularized logistic regression and random forest. You’ll discover how to tune algorithms to provide the most accurate predictions on new and unseen data. As you progress, you’ll gain insights into the working and output of these algorithms, building your understanding of both the predictive capabilities of the models and why they make these predictions.By then end of this book, you will have the necessary skills to confidently use machine learning algorithms to perform detailed data analysis and extract meaningful insights from unstructured data.What you will learnInstall the required packages to set up a data science coding environmentLoad data into a Jupyter notebook running PythonUse Matplotlib to create data visualizationsFit machine learning models using scikit-learnUse lasso and ridge regression to regularize your modelsCompare performance between models to find the best outcomesUse k-fold cross-validation to select model hyperparametersWho this book is forIf you are a data analyst, data scientist, or business analyst who wants to get started using Python and machine learning techniques to analyze data and predict outcomes, this book is for you. Basic knowledge of Python and data analytics will help you get the most from this book. Familiarity with mathematical concepts such as algebra and basic statistics will also be useful.
R 1,335.00
Programming with MicroPython
It’s an exciting time to get involved with MicroPython, the re-implementation of Python 3 for microcontrollers and embedded systems. This practical guide delivers the knowledge you need to roll up your sleeves and create exceptional embedded projects with this lean and efficient programming language. If you’re familiar with Python as a programmer, educator, or maker, you’re ready to learn—and have fun along the way. Author Nicholas Tollervey takes you on a journey from first steps to advanced projects. You’ll explore the types of devices that run MicroPython, and examine how the language uses and interacts with hardware to process input, connect to the outside world, communicate wirelessly, make sounds and music, and drive robotics projects. Work with MicroPython on four typical devices: PyBoard, the micro:bit, Adafruit’s Circuit Playground Express, and ESP8266/ESP32 boards Explore a framework that helps you generate, evaluate, and evolve embedded projects that solve real problems Dive into practical MicroPython examples: visual feedback, input and sensing, GPIO, networking, sound and music, and robotics Learn how idiomatic MicroPython helps you express a lot with the minimum of resources Take the next step by getting involved with the Python community
R 1,730.00
OpenCV 3.x with Python By Example
Learn the techniques for object recognition, 3D reconstruction, stereo imaging, and other computer vision applications using examples on different functions of OpenCV.Key Features Learn how to apply complex visual effects to images with OpenCV 3.x and Python Extract features from an image and use them to develop advanced applications Build algorithms to help you understand image content and perform visual searches Get to grips with advanced techniques in OpenCV such as machine learning, artificial neural network, 3D reconstruction, and augmented realityBook DescriptionComputer vision is found everywhere in modern technology. OpenCV for Python enables us to run computer vision algorithms in real time. With the advent of powerful machines, we have more processing power to work with. Using this technology, we can seamlessly integrate our computer vision applications into the cloud. Focusing on OpenCV 3.x and Python 3.6, this book will walk you through all the building blocks needed to build amazing computer vision applications with ease.We start off by manipulating images using simple filtering and geometric transformations. We then discuss affine and projective transformations and see how we can use them to apply cool advanced manipulations to your photos like resizing them while keeping the content intact or smoothly removing undesired elements. We will then cover techniques of object tracking, body part recognition, and object recognition using advanced techniques of machine learning such as artificial neural network. 3D reconstruction and augmented reality techniques are also included. The book covers popular OpenCV libraries with the help of examples.This book is a practical tutorial that covers various examples at different levels, teaching you about the different functions of OpenCV and their actual implementation. By the end of this book, you will have acquired the skills to use OpenCV and Python to develop real-world computer vision applications.What you will learn Detect shapes and edges from images and videos How to apply filters on images and videos Use different techniques to manipulate and improve images Extract and manipulate particular parts of images and videos Track objects or colors from videos Recognize specific object or faces from images and videos How to create Augmented Reality applications Apply artificial neural networks and machine learning to improve object recognitionWho this book is forThis book is intended for Python developers who are new to OpenCV and want to develop computer vision applications with OpenCV and Python. This book is also useful for generic software developers who want to deploy computer vision applications on the cloud. It would be helpful to have some familiarity with basic mathematical concepts such as vectors, matrices, and so on.
R 1,661.00
Learning Geospatial Analysis with Python
This is a tutorial-style book that helps you to perform Geospatial and GIS analysis with Python and its tools/libraries. This book will first introduce various Python-related tools/packages in the initial chapters before moving towards practical usage, examples, and implementation in specialized kinds of Geospatial data analysis. This book is for anyone who wants to understand digital mapping and analysis and who uses Python or another scripting language for automation or crunching data manually.This book primarily targets Python developers, researchers, and analysts who want to perform Geospatial, modeling, and GIS analysis with Python.
R 1,889.00
IPython Interactive Computing and Visualization Cookbook
Intended to anyone interested in numerical computing and data science: students, researchers, teachers, engineers, analysts, hobbyists...Basic knowledge of Python/NumPy is recommended. Some skills in mathematics will help you understand the theory behind the computational methods.
R 1,889.00
Foundations of PyGTK Development
There are only two mainstream solutions for building the graphical interface of Linux-based desktop applications, and GTK+ (GIMP Toolkit) is one of them. It is a necessary technology for all Linux programmers. This book guides the reader through the complexities of GTK+, laying the groundwork that allows the reader to make the leap from novice to professional. Beginning with an overview of key topics such as widget choice, placement, and behavior, readers move on to learn about more advanced issues. Replete with real-world examples, the developer can quickly take advantages of the concepts presented within to begin building his own projects.
R 1,654.59
