Learning Data Mining with Python. Harness the power of Python to analyze data and create insightful predictive models

Robert Layton, Robert Layton, Ari Chanen

Learning Data Mining with Python. Use Python to manipulate data and build predictive models - Second Edition

Robert Layton

This book teaches you to design and develop data mining applications using a variety of datasets, starting with basic classification and affinity analysis. This book covers a large number of libraries available in Python, including the Jupyter Notebook, pandas, scikit-learn, and NLTK. You will gain hands on experience with complex data types including text, images, and graphs. You will also discover object detection using Deep Neural Networks, which is one of the big, difficult areas of machine learning right now.With restructured examples and code samples updated for the latest edition of Python, each chapter of this book introduces you to new algorithms and techniques. By the end of the book, you will have great insights into using Python for data mining and understanding of the algorithms as well as implementations.

Learning Geospatial Analysis with Python. Understand GIS fundamentals and perform remote sensing data analysis using Python 3.7 - Third Edition

Joel Lawhead

Geospatial analysis is used in almost every domain you can think of, including defense, farming, and even medicine. With this systematic guide, you'll get started with geographic information system (GIS) and remote sensing analysis using the latest features in Python.This book will take you through GIS techniques, geodatabases, geospatial raster data, and much more using the latest built-in tools and libraries in Python 3.7. You'll learn everything you need to know about using software packages or APIs and generic algorithms that can be used for different situations. Furthermore, you'll learn how to apply simple Python GIS geospatial processes to a variety of problems, and work with remote sensing data.By the end of the book, you'll be able to build a generic corporate system, which can be implemented in any organization to manage customer support requests and field support personnel.

Learning Julia. Build high-performance applications for scientific computing

Anshul Joshi, Rahul Lakhanpal

Julia is a highly appropriate language for scientific computing, but it comes with all the required capabilities of a general-purpose language. It allows us to achieve C/Fortran-like performance while maintaining the concise syntax of a scripting language such as Python. It is perfect for building high-performance and concurrent applications. From the basics of its syntax to learning built-in object types, this book covers it all.This book shows you how to write effective functions, reduce code redundancies, and improve code reuse. It will be helpful for new programmers who are starting out with Julia to explore its wide and ever-growing package ecosystem and also for experienced developers/statisticians/data scientists who want to add Julia to their skill-set.The book presents the fundamentals of programming in Julia and in-depth informative examples, using a step-by-step approach. You will be taken through concepts and examples such as doing simple mathematical operations, creating loops, metaprogramming, functions, collections, multiple dispatch, and so on.By the end of the book, you will be able to apply your skills in Julia to create and explore applications of any domain.

Learning Jupyter 5. Explore interactive computing using Python, Java, JavaScript, R, Julia, and JupyterLab - Second Edition

Dan Toomey

The Jupyter Notebook allows you to create and share documents that contain live code, equations, visualizations, and explanatory text. The Jupyter Notebook system is extensively used in domains such as data cleaning and transformation, numerical simulation, statistical modeling, and machine learning. Learning Jupyter 5 will help you get to grips with interactive computing using real-world examples.The book starts with a detailed overview of the Jupyter Notebook system and its installation in different environments. Next, you will learn to integrate the Jupyter system with different programming languages such as R, Python, Java, JavaScript, and Julia, and explore various versions and packages that are compatible with the Notebook system. Moving ahead, you will master interactive widgets and namespaces and work with Jupyter in a multi-user mode.By the end of this book, you will have used Jupyter with a big dataset and be able to apply all the functionalities you’ve explored throughout the book. You will also have learned all about the Jupyter Notebook and be able to start performing data transformation, numerical simulation, and data visualization.

Learning OpenCV 4 Computer Vision with Python 3. Get to grips with tools, techniques, and algorithms for computer vision and machine learning - Third Edition

Joseph Howse, Joe Minichino

Computer vision is a rapidly evolving science, encompassing diverse applications and techniques. This book will not only help those who are getting started with computer vision but also experts in the domain. You’ll be able to put theory into practice by building apps with OpenCV 4 and Python 3.You’ll start by understanding OpenCV 4 and how to set it up with Python 3 on various platforms. Next, you’ll learn how to perform basic operations such as reading, writing, manipulating, and displaying still images, videos, and camera feeds. From taking you through image processing, video analysis, and depth estimation and segmentation, to helping you gain practice by building a GUI app, this book ensures you’ll have opportunities for hands-on activities. Next, you’ll tackle two popular challenges: face detection and face recognition. You’ll also learn about object classification and machine learning concepts, which will enable you to create and use object detectors and classifiers, and even track objects in movies or video camera feed. Later, you’ll develop your skills in 3D tracking and augmented reality. Finally, you’ll cover ANNs and DNNs, learning how to develop apps for recognizing handwritten digits and classifying a person's gender and age.By the end of this book, you’ll have the skills you need to execute real-world computer vision projects.

Learning OpenStack Networking. Build a solid foundation in virtual networking technologies for OpenStack-based clouds - Third Edition

James Denton

OpenStack Networking is a pluggable, scalable, and API-driven system to manage physical and virtual networking resources in an OpenStack-based cloud. Like other core OpenStack components, OpenStack Networking can be used by administrators and users to increase the value and maximize the use of existing datacenter resources. This third edition of Learning OpenStack Networking walks you through the installation of OpenStack and provides you with a foundation that can be used to build a scalable and production-ready OpenStack cloud.In the initial chapters, you will review the physical network requirements and architectures necessary for an OpenStack environment that provide core cloud functionality. Then, you’ll move through the installation of the new release of OpenStack using packages from the Ubuntu repository. An overview of Neutron networking foundational concepts, including networks, subnets, and ports will segue into advanced topics such as security groups, distributed virtual routers, virtual load balancers, and VLAN tagging within instances.By the end of this book, you will have built a network infrastructure for your cloud using OpenStack Neutron.

Learning pandas. High performance data manipulation and analysis using Python - Second Edition

Michael Heydt

You will learn how to use pandas to perform data analysis in Python. You will start with an overview of data analysis and iteratively progress from modeling data, to accessing data from remote sources, performing numeric and statistical analysis, through indexing and performing aggregate analysis, and finally to visualizing statistical data and applying pandas to finance.With the knowledge you gain from this book, you will quickly learn pandas and how it can empower you in the exciting world of data manipulation, analysis and science.