Hands On Enterprise Automation With Python

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Hands-On Enterprise Automation with Python

Author : Bassem Aly
Publisher : Packt Publishing Ltd
ISBN 13 : 1788992644
Total Pages : 383 pages
Book Rating : 4.7/5 (889 download)

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Book Synopsis Hands-On Enterprise Automation with Python by : Bassem Aly

Download or read book Hands-On Enterprise Automation with Python written by Bassem Aly and published by Packt Publishing Ltd. This book was released on 2018-06-28 with total page 383 pages. Available in PDF, EPUB and Kindle. Book excerpt: Invent your own Python scripts to automate your infrastructure Key Features Make the most of Python libraries and modules to automate your infrastructure Leverage Python programming to automate server configurations and administration tasks Efficiently develop your Python skill set Book Description Hands-On Enterprise Automation with Python starts by covering the set up of a Python environment to perform automation tasks, as well as the modules, libraries, and tools you will be using. We’ll explore examples of network automation tasks using simple Python programs and Ansible. Next, we will walk you through automating administration tasks with Python Fabric, where you will learn to perform server configuration and administration, along with system administration tasks such as user management, database management, and process management. As you progress through this book, you’ll automate several testing services with Python scripts and perform automation tasks on virtual machines and cloud infrastructure with Python. In the concluding chapters, you will cover Python-based offensive security tools and learn how to automate your security tasks. By the end of this book, you will have mastered the skills of automating several system administration tasks with Python. What you will learn Understand common automation modules used in Python Develop Python scripts to manage network devices Automate common Linux administration tasks with Ansible and Fabric Managing Linux processes Administrate VMware, OpenStack, and AWS instances with Python Security automation and sharing code on GitHub Who this book is for Hands-On Enterprise Automation with Python is for system administrators and DevOps engineers who are looking for an alternative to major automation frameworks such as Puppet and Chef. Basic programming knowledge with Python and Linux shell scripting is necessary.

Hands-On Enterprise Application Development with Python

Author : Saurabh Badhwar
Publisher : Packt Publishing Ltd
ISBN 13 : 1789530636
Total Pages : 362 pages
Book Rating : 4.7/5 (895 download)

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Book Synopsis Hands-On Enterprise Application Development with Python by : Saurabh Badhwar

Download or read book Hands-On Enterprise Application Development with Python written by Saurabh Badhwar and published by Packt Publishing Ltd. This book was released on 2018-12-28 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: Architect scalable, reliable, and maintainable applications for enterprises with Python Key FeaturesExplore various Python design patterns used for enterprise software developmentApply best practices for testing and performance optimization to build stable applicationsLearn about different attacking strategies used on enterprise applications and how to avoid themBook Description Dynamically typed languages like Python are continuously improving. With the addition of exciting new features and a wide selection of modern libraries and frameworks, Python has emerged as an ideal language for developing enterprise applications. Hands-On Enterprise Application Development with Python will show you how to build effective applications that are stable, secure, and easily scalable. The book is a detailed guide to building an end-to-end enterprise-grade application in Python. You will learn how to effectively implement Python features and design patterns that will positively impact your application lifecycle. The book also covers advanced concurrency techniques that will help you build a RESTful application with an optimized frontend. Given that security and stability are the foundation for an enterprise application, you’ll be trained on effective testing, performance analysis, and security practices, and understand how to embed them in your codebase during the initial phase. You’ll also be guided in how to move on from a monolithic architecture to one that is service oriented, leveraging microservices and serverless deployment techniques. By the end of the book, you will have become proficient at building efficient enterprise applications in Python. What you will learnUnderstand the purpose of design patterns and their impact on application lifecycleBuild applications that can handle large amounts of data-intensive operationsUncover advanced concurrency techniques and discover how to handle a large number of requests in productionOptimize frontends to improve the client-side experience of your applicationEffective testing and performance profiling techniques to detect issues in applications early in the development cycleBuild applications with a focus on securityImplement large applications as microservices to improve scalabilityWho this book is for If you’re a developer who wants to build enterprise-grade applications, this book is for you. Basic to intermediate-level of programming experience with Python and database systems is required to understand the concepts covered in this book.

Hands-On Software Engineering with Python

Author : Brian Allbee
Publisher : Packt Publishing Ltd
ISBN 13 : 1788621352
Total Pages : 736 pages
Book Rating : 4.7/5 (886 download)

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Book Synopsis Hands-On Software Engineering with Python by : Brian Allbee

Download or read book Hands-On Software Engineering with Python written by Brian Allbee and published by Packt Publishing Ltd. This book was released on 2018-10-26 with total page 736 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore various verticals in software engineering through high-end systems using Python Key FeaturesMaster the tools and techniques used in software engineeringEvaluates available database options and selects one for the final Central Office system-componentsExperience the iterations software go through and craft enterprise-grade systemsBook Description Software Engineering is about more than just writing code—it includes a host of soft skills that apply to almost any development effort, no matter what the language, development methodology, or scope of the project. Being a senior developer all but requires awareness of how those skills, along with their expected technical counterparts, mesh together through a project's life cycle. This book walks you through that discovery by going over the entire life cycle of a multi-tier system and its related software projects. You'll see what happens before any development takes place, and what impact the decisions and designs made at each step have on the development process. The development of the entire project, over the course of several iterations based on real-world Agile iterations, will be executed, sometimes starting from nothing, in one of the fastest growing languages in the world—Python. Application of practices in Python will be laid out, along with a number of Python-specific capabilities that are often overlooked. Finally, the book will implement a high-performance computing solution, from first principles through complete foundation. What you will learnUnderstand what happens over the course of a system's life (SDLC)Establish what to expect from the pre-development life cycle stepsFind out how the development-specific phases of the SDLC affect developmentUncover what a real-world development process might be like, in an Agile wayFind out how to do more than just write the codeIdentify the existence of project-independent best practices and how to use themFind out how to design and implement a high-performance computing processWho this book is for Hands-On Software Engineering with Python is for you if you are a developer having basic understanding of programming and its paradigms and want to skill up as a senior programmer. It is assumed that you have basic Python knowledge.

pytest Quick Start Guide

Author : Bruno Oliveira
Publisher : Packt Publishing Ltd
ISBN 13 : 1789343828
Total Pages : 153 pages
Book Rating : 4.7/5 (893 download)

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Book Synopsis pytest Quick Start Guide by : Bruno Oliveira

Download or read book pytest Quick Start Guide written by Bruno Oliveira and published by Packt Publishing Ltd. This book was released on 2018-08-29 with total page 153 pages. Available in PDF, EPUB and Kindle. Book excerpt: Python's built-in unittest module is showing it's age; hard to extend, debug and track what's going on. The pytest framework overcomes these problems and simplifies testing your Python software. Many users love to use pytest and the improvement in their testing shows! This book is the ideal introduction to pytest, teaching you how to write ...

Python Automation Cookbook

Author : Jaime Buelta
Publisher : Packt Publishing Ltd
ISBN 13 : 1800202598
Total Pages : 527 pages
Book Rating : 4.8/5 (2 download)

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Book Synopsis Python Automation Cookbook by : Jaime Buelta

Download or read book Python Automation Cookbook written by Jaime Buelta and published by Packt Publishing Ltd. This book was released on 2020-05-29 with total page 527 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get a firm grip on the core processes including browser automation, web scraping, Word, Excel, and GUI automation with Python 3.8 and higher Key FeaturesAutomate integral business processes such as report generation, email marketing, and lead generationExplore automated code testing and Python’s growth in data science and AI automation in three new chaptersUnderstand techniques to extract information and generate appealing graphs, and reports with MatplotlibBook Description In this updated and extended version of Python Automation Cookbook, each chapter now comprises the newest recipes and is revised to align with Python 3.8 and higher. The book includes three new chapters that focus on using Python for test automation, machine learning projects, and for working with messy data. This edition will enable you to develop a sharp understanding of the fundamentals required to automate business processes through real-world tasks, such as developing your first web scraping application, analyzing information to generate spreadsheet reports with graphs, and communicating with automatically generated emails. Once you grasp the basics, you will acquire the practical knowledge to create stunning graphs and charts using Matplotlib, generate rich graphics with relevant information, automate marketing campaigns, build machine learning projects, and execute debugging techniques. By the end of this book, you will be proficient in identifying monotonous tasks and resolving process inefficiencies to produce superior and reliable systems. What you will learnLearn data wrangling with Python and Pandas for your data science and AI projectsAutomate tasks such as text classification, email filtering, and web scraping with PythonUse Matplotlib to generate a variety of stunning graphs, charts, and mapsAutomate a range of report generation tasks, from sending SMS and email campaigns to creating templates, adding images in Word, and even encrypting PDFsMaster web scraping and web crawling of popular file formats and directories with tools like Beautiful SoupBuild cool projects such as a Telegram bot for your marketing campaign, a reader from a news RSS feed, and a machine learning model to classify emails to the correct department based on their contentCreate fire-and-forget automation tasks by writing cron jobs, log files, and regexes with Python scriptingWho this book is for Python Automation Cookbook - Second Edition is for developers, data enthusiasts or anyone who wants to automate monotonous manual tasks related to business processes such as finance, sales, and HR, among others. Working knowledge of Python is all you need to get started with this book.

Hands-On Data Science and Python Machine Learning

Author : Frank Kane
Publisher : Packt Publishing Ltd
ISBN 13 : 1787280225
Total Pages : 420 pages
Book Rating : 4.7/5 (872 download)

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Book Synopsis Hands-On Data Science and Python Machine Learning by : Frank Kane

Download or read book Hands-On Data Science and Python Machine Learning written by Frank Kane and published by Packt Publishing Ltd. This book was released on 2017-07-31 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the fundamentals of machine learning with Python in a concise and dynamic manner. It covers data mining and large-scale machine learning using Apache Spark. About This Book Take your first steps in the world of data science by understanding the tools and techniques of data analysis Train efficient Machine Learning models in Python using the supervised and unsupervised learning methods Learn how to use Apache Spark for processing Big Data efficiently Who This Book Is For If you are a budding data scientist or a data analyst who wants to analyze and gain actionable insights from data using Python, this book is for you. Programmers with some experience in Python who want to enter the lucrative world of Data Science will also find this book to be very useful, but you don't need to be an expert Python coder or mathematician to get the most from this book. What You Will Learn Learn how to clean your data and ready it for analysis Implement the popular clustering and regression methods in Python Train efficient machine learning models using decision trees and random forests Visualize the results of your analysis using Python's Matplotlib library Use Apache Spark's MLlib package to perform machine learning on large datasets In Detail Join Frank Kane, who worked on Amazon and IMDb's machine learning algorithms, as he guides you on your first steps into the world of data science. Hands-On Data Science and Python Machine Learning gives you the tools that you need to understand and explore the core topics in the field, and the confidence and practice to build and analyze your own machine learning models. With the help of interesting and easy-to-follow practical examples, Frank Kane explains potentially complex topics such as Bayesian methods and K-means clustering in a way that anybody can understand them. Based on Frank's successful data science course, Hands-On Data Science and Python Machine Learning empowers you to conduct data analysis and perform efficient machine learning using Python. Let Frank help you unearth the value in your data using the various data mining and data analysis techniques available in Python, and to develop efficient predictive models to predict future results. You will also learn how to perform large-scale machine learning on Big Data using Apache Spark. The book covers preparing your data for analysis, training machine learning models, and visualizing the final data analysis. Style and approach This comprehensive book is a perfect blend of theory and hands-on code examples in Python which can be used for your reference at any time.

Hands-On Reactive Programming with Python

Author : Romain Picard
Publisher : Packt Publishing Ltd
ISBN 13 : 1789132754
Total Pages : 411 pages
Book Rating : 4.7/5 (891 download)

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Book Synopsis Hands-On Reactive Programming with Python by : Romain Picard

Download or read book Hands-On Reactive Programming with Python written by Romain Picard and published by Packt Publishing Ltd. This book was released on 2018-10-25 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive guide to help you understand the principles of Reactive and asynchronous programming and its benefits Key FeaturesExplore the advantages of Reactive programmingUse concurrency and parallelism in RxPY to build powerful reactive applicationsDeploy and scale your reactive applications using DockerBook Description Reactive programming is central to many concurrent systems, but it’s famous for its steep learning curve, which makes most developers feel like they're hitting a wall. With this book, you will get to grips with reactive programming by steadily exploring various concepts This hands-on guide gets you started with Reactive Programming (RP) in Python. You will learn abouta the principles and benefits of using RP, which can be leveraged to build powerful concurrent applications. As you progress through the chapters, you will be introduced to the paradigm of Functional and Reactive Programming (FaRP), observables and observers, and concurrency and parallelism. The book will then take you through the implementation of an audio transcoding server and introduce you to a library that helps in the writing of FaRP code. You will understand how to use third-party services and dynamically reconfigure an application. By the end of the book, you will also have learned how to deploy and scale your applications with Docker and Traefik and explore the significant potential behind the reactive streams concept, and you'll have got to grips with a comprehensive set of best practices. What you will learnStructure Python code for better readability, testing, and performanceExplore the world of event-based programmingGrasp the use of the most common operators in RxUnderstand reactive extensions beyond simple examplesMaster the art of writing reusable componentsDeploy an application on a cloud platform with Docker and TraefikWho this book is for If you are a Python developer who wants to learn Reactive programming to build powerful concurrent and asynchronous applications, this book is for you. Basic understanding of the Python language is all you need to understand the concepts covered in this book.

Hands-On Transfer Learning with Python

Author : Dipanjan Sarkar
Publisher : Packt Publishing Ltd
ISBN 13 : 1788839056
Total Pages : 430 pages
Book Rating : 4.7/5 (888 download)

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Book Synopsis Hands-On Transfer Learning with Python by : Dipanjan Sarkar

Download or read book Hands-On Transfer Learning with Python written by Dipanjan Sarkar and published by Packt Publishing Ltd. This book was released on 2018-08-31 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning simplified by taking supervised, unsupervised, and reinforcement learning to the next level using the Python ecosystem Key Features Build deep learning models with transfer learning principles in Python implement transfer learning to solve real-world research problems Perform complex operations such as image captioning neural style transfer Book Description Transfer learning is a machine learning (ML) technique where knowledge gained during training a set of problems can be used to solve other similar problems. The purpose of this book is two-fold; firstly, we focus on detailed coverage of deep learning (DL) and transfer learning, comparing and contrasting the two with easy-to-follow concepts and examples. The second area of focus is real-world examples and research problems using TensorFlow, Keras, and the Python ecosystem with hands-on examples. The book starts with the key essential concepts of ML and DL, followed by depiction and coverage of important DL architectures such as convolutional neural networks (CNNs), deep neural networks (DNNs), recurrent neural networks (RNNs), long short-term memory (LSTM), and capsule networks. Our focus then shifts to transfer learning concepts, such as model freezing, fine-tuning, pre-trained models including VGG, inception, ResNet, and how these systems perform better than DL models with practical examples. In the concluding chapters, we will focus on a multitude of real-world case studies and problems associated with areas such as computer vision, audio analysis and natural language processing (NLP). By the end of this book, you will be able to implement both DL and transfer learning principles in your own systems. What you will learn Set up your own DL environment with graphics processing unit (GPU) and Cloud support Delve into transfer learning principles with ML and DL models Explore various DL architectures, including CNN, LSTM, and capsule networks Learn about data and network representation and loss functions Get to grips with models and strategies in transfer learning Walk through potential challenges in building complex transfer learning models from scratch Explore real-world research problems related to computer vision and audio analysis Understand how transfer learning can be leveraged in NLP Who this book is for Hands-On Transfer Learning with Python is for data scientists, machine learning engineers, analysts and developers with an interest in data and applying state-of-the-art transfer learning methodologies to solve tough real-world problems. Basic proficiency in machine learning and Python is required.

Introduction to Python Network Automation

Author : Brendan Choi
Publisher : Apress
ISBN 13 : 9781484268056
Total Pages : 490 pages
Book Rating : 4.2/5 (68 download)

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Book Synopsis Introduction to Python Network Automation by : Brendan Choi

Download or read book Introduction to Python Network Automation written by Brendan Choi and published by Apress. This book was released on 2021-05-23 with total page 490 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn and implement network automation within the Enterprise network using Python 3. This introductory book will be your guide to building an integrated virtual networking lab to begin your Network Automation journey and master the basics of Python Network Automation. The book features a review of the practical Python network automation scripting skills and tips learned from the production network, so you can safely test and practice in a lab environment first, various Python modules such as paramiko and netmiko, pandas, re, and much more. You'll also develop essential skills such as Python scripting, regular expressions, Linux and Windows administration, VMware virtualization, and Cisco networking from the comfort of your laptop/PC with no actual networking hardware. Finally, you will learn to write a fully automated and working Cisco IOS XE upgrade application using Python. Introduction to Python Network Automation uses a canonical order, where you begin at the bottom and by the time you have completed this book, you will at least reach the intermediate level of Python coding for enterprise networking automation using native Python tools. What You'll Learn Build a proper GNS3-based networking lab for Python network automation needs. Write the basics of Python codes in both the Windows and Linux environments. Control network devices using telnet, SSH, and SNMP protocols using Python codes. Understand virtualization and how to use VMware workstation Examine virtualization and how to use VMware Workstation Pro Develop a working Cisco IOS upgrade application Who This Book Is For IT Engineers and developers, network managers and students, who would like to learn network automation using Python.

Practical Network Automation

Author : Abhishek Ratan
Publisher : Packt Publishing Ltd
ISBN 13 : 1788299132
Total Pages : 260 pages
Book Rating : 4.7/5 (882 download)

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Book Synopsis Practical Network Automation by : Abhishek Ratan

Download or read book Practical Network Automation written by Abhishek Ratan and published by Packt Publishing Ltd. This book was released on 2017-11-16 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get More from your Network with Automation tools to increase its effectiveness. About This Book Get started with network automation (and different automation tasks) with relevant use cases Apply software design principles such as Continuous Integration and DevOps to your network toolkit Guides you through some best practices in automation Who This Book Is For If you are a network engineer looking for an extensive guide to help you automate and manage your network efficiently, then this book is for you. What You Will Learn Get the detailed analysis of Network automation Trigger automations through available data factors Improve data center robustness and security through specific access and data digging Get an Access to APIs from Excel for dynamic reporting Set up a communication with SSH-based devices using netmiko Make full use of practical use cases and best practices to get accustomed with the various aspects of network automation In Detail Network automation is the use of IT controls to supervise and carry out every-day network management functions. It plays a key role in network virtualization technologies and network functions. The book starts by providing an introduction to network automation, SDN, and its applications, which include integrating DevOps tools to automate the network efficiently. It then guides you through different network automation tasks and covers various data digging and reporting methodologies such as IPv6 migration, DC relocations, and interface parsing, all the while retaining security and improving data center robustness. The book then moves on to the use of Python and the management of SSH keys for machine-to-machine (M2M) communication, all followed by practical use cases. The book also covers the importance of Ansible for network automation including best practices in automation, ways to test automated networks using different tools, and other important techniques. By the end of the book, you will be well acquainted with the various aspects of network automation. Style and approach A clear, concise, and straightforward book that will enable you to automate networks and improve performance.

Hands-On Predictive Analytics with Python

Author : Alvaro Fuentes
Publisher : Packt Publishing Ltd
ISBN 13 : 1789134544
Total Pages : 320 pages
Book Rating : 4.7/5 (891 download)

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Book Synopsis Hands-On Predictive Analytics with Python by : Alvaro Fuentes

Download or read book Hands-On Predictive Analytics with Python written by Alvaro Fuentes and published by Packt Publishing Ltd. This book was released on 2018-12-28 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Step-by-step guide to build high performing predictive applications Key FeaturesUse the Python data analytics ecosystem to implement end-to-end predictive analytics projectsExplore advanced predictive modeling algorithms with an emphasis on theory with intuitive explanationsLearn to deploy a predictive model's results as an interactive applicationBook Description Predictive analytics is an applied field that employs a variety of quantitative methods using data to make predictions. It involves much more than just throwing data onto a computer to build a model. This book provides practical coverage to help you understand the most important concepts of predictive analytics. Using practical, step-by-step examples, we build predictive analytics solutions while using cutting-edge Python tools and packages. The book's step-by-step approach starts by defining the problem and moves on to identifying relevant data. We will also be performing data preparation, exploring and visualizing relationships, building models, tuning, evaluating, and deploying model. Each stage has relevant practical examples and efficient Python code. You will work with models such as KNN, Random Forests, and neural networks using the most important libraries in Python's data science stack: NumPy, Pandas, Matplotlib, Seaborn, Keras, Dash, and so on. In addition to hands-on code examples, you will find intuitive explanations of the inner workings of the main techniques and algorithms used in predictive analytics. By the end of this book, you will be all set to build high-performance predictive analytics solutions using Python programming. What you will learnGet to grips with the main concepts and principles of predictive analyticsLearn about the stages involved in producing complete predictive analytics solutionsUnderstand how to define a problem, propose a solution, and prepare a datasetUse visualizations to explore relationships and gain insights into the datasetLearn to build regression and classification models using scikit-learnUse Keras to build powerful neural network models that produce accurate predictionsLearn to serve a model's predictions as a web applicationWho this book is for This book is for data analysts, data scientists, data engineers, and Python developers who want to learn about predictive modeling and would like to implement predictive analytics solutions using Python's data stack. People from other backgrounds who would like to enter this exciting field will greatly benefit from reading this book. All you need is to be proficient in Python programming and have a basic understanding of statistics and college-level algebra.

Hands-On Genetic Algorithms with Python

Author : Eyal Wirsansky
Publisher : Packt Publishing Ltd
ISBN 13 : 1838559183
Total Pages : 334 pages
Book Rating : 4.8/5 (385 download)

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Book Synopsis Hands-On Genetic Algorithms with Python by : Eyal Wirsansky

Download or read book Hands-On Genetic Algorithms with Python written by Eyal Wirsansky and published by Packt Publishing Ltd. This book was released on 2020-01-31 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore the ever-growing world of genetic algorithms to solve search, optimization, and AI-related tasks, and improve machine learning models using Python libraries such as DEAP, scikit-learn, and NumPy Key FeaturesExplore the ins and outs of genetic algorithms with this fast-paced guideImplement tasks such as feature selection, search optimization, and cluster analysis using PythonSolve combinatorial problems, optimize functions, and enhance the performance of artificial intelligence applicationsBook Description Genetic algorithms are a family of search, optimization, and learning algorithms inspired by the principles of natural evolution. By imitating the evolutionary process, genetic algorithms can overcome hurdles encountered in traditional search algorithms and provide high-quality solutions for a variety of problems. This book will help you get to grips with a powerful yet simple approach to applying genetic algorithms to a wide range of tasks using Python, covering the latest developments in artificial intelligence. After introducing you to genetic algorithms and their principles of operation, you'll understand how they differ from traditional algorithms and what types of problems they can solve. You'll then discover how they can be applied to search and optimization problems, such as planning, scheduling, gaming, and analytics. As you advance, you'll also learn how to use genetic algorithms to improve your machine learning and deep learning models, solve reinforcement learning tasks, and perform image reconstruction. Finally, you'll cover several related technologies that can open up new possibilities for future applications. By the end of this book, you'll have hands-on experience of applying genetic algorithms in artificial intelligence as well as in numerous other domains. What you will learnUnderstand how to use state-of-the-art Python tools to create genetic algorithm-based applicationsUse genetic algorithms to optimize functions and solve planning and scheduling problemsEnhance the performance of machine learning models and optimize deep learning network architectureApply genetic algorithms to reinforcement learning tasks using OpenAI GymExplore how images can be reconstructed using a set of semi-transparent shapesDiscover other bio-inspired techniques, such as genetic programming and particle swarm optimizationWho this book is for This book is for software developers, data scientists, and AI enthusiasts who want to use genetic algorithms to carry out intelligent tasks in their applications. Working knowledge of Python and basic knowledge of mathematics and computer science will help you get the most out of this book.

Network Programmability and Automation

Author : Jason Edelman
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491931310
Total Pages : 842 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis Network Programmability and Automation by : Jason Edelman

Download or read book Network Programmability and Automation written by Jason Edelman and published by "O'Reilly Media, Inc.". This book was released on 2018-02-02 with total page 842 pages. Available in PDF, EPUB and Kindle. Book excerpt: Like sysadmins before them, network engineers are finding that they cannot do their work manually anymore. As the field faces new protocols, technologies, delivery models, and a pressing need for businesses to be more agile and flexible, network automation is becoming essential. This practical guide shows network engineers how to use a range of technologies and tools—including Linux, Python, JSON, and XML—to automate their systems through code. Network programming and automation will help you simplify tasks involved in configuring, managing, and operating network equipment, topologies, services, and connectivity. Through the course of the book, you’ll learn the basic skills and tools you need to make this critical transition. This book covers: Python programming basics: data types, conditionals, loops, functions, classes, and modules Linux fundamentals to provide the foundation you need on your network automation journey Data formats and models: JSON, XML, YAML, and YANG for networking Jinja templating and its applicability for creating network device configurations The role of application programming interfaces (APIs) in network automation Source control with Git to manage code changes during the automation process How Ansible, Salt, and StackStorm open source automation tools can be used to automate network devices Key tools and technologies required for a Continuous Integration (CI) pipeline in network operations

Hands-On Exploratory Data Analysis with Python

Author : Suresh Kumar Mukhiya
Publisher : Packt Publishing Ltd
ISBN 13 : 178953562X
Total Pages : 342 pages
Book Rating : 4.7/5 (895 download)

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Book Synopsis Hands-On Exploratory Data Analysis with Python by : Suresh Kumar Mukhiya

Download or read book Hands-On Exploratory Data Analysis with Python written by Suresh Kumar Mukhiya and published by Packt Publishing Ltd. This book was released on 2020-03-27 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover techniques to summarize the characteristics of your data using PyPlot, NumPy, SciPy, and pandas Key FeaturesUnderstand the fundamental concepts of exploratory data analysis using PythonFind missing values in your data and identify the correlation between different variablesPractice graphical exploratory analysis techniques using Matplotlib and the Seaborn Python packageBook Description Exploratory Data Analysis (EDA) is an approach to data analysis that involves the application of diverse techniques to gain insights into a dataset. This book will help you gain practical knowledge of the main pillars of EDA - data cleaning, data preparation, data exploration, and data visualization. You’ll start by performing EDA using open source datasets and perform simple to advanced analyses to turn data into meaningful insights. You’ll then learn various descriptive statistical techniques to describe the basic characteristics of data and progress to performing EDA on time-series data. As you advance, you’ll learn how to implement EDA techniques for model development and evaluation and build predictive models to visualize results. Using Python for data analysis, you’ll work with real-world datasets, understand data, summarize its characteristics, and visualize it for business intelligence. By the end of this EDA book, you’ll have developed the skills required to carry out a preliminary investigation on any dataset, yield insights into data, present your results with visual aids, and build a model that correctly predicts future outcomes. What you will learnImport, clean, and explore data to perform preliminary analysis using powerful Python packagesIdentify and transform erroneous data using different data wrangling techniquesExplore the use of multiple regression to describe non-linear relationshipsDiscover hypothesis testing and explore techniques of time-series analysisUnderstand and interpret results obtained from graphical analysisBuild, train, and optimize predictive models to estimate resultsPerform complex EDA techniques on open source datasetsWho this book is for This EDA book is for anyone interested in data analysis, especially students, statisticians, data analysts, and data scientists. The practical concepts presented in this book can be applied in various disciplines to enhance decision-making processes with data analysis and synthesis. Fundamental knowledge of Python programming and statistical concepts is all you need to get started with this book.

Hands-On Q-Learning with Python

Author : Nazia Habib
Publisher : Packt Publishing Ltd
ISBN 13 : 1789345758
Total Pages : 200 pages
Book Rating : 4.7/5 (893 download)

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Book Synopsis Hands-On Q-Learning with Python by : Nazia Habib

Download or read book Hands-On Q-Learning with Python written by Nazia Habib and published by Packt Publishing Ltd. This book was released on 2019-04-19 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage the power of reward-based training for your deep learning models with Python Key FeaturesUnderstand Q-learning algorithms to train neural networks using Markov Decision Process (MDP)Study practical deep reinforcement learning using Q-NetworksExplore state-based unsupervised learning for machine learning modelsBook Description Q-learning is a machine learning algorithm used to solve optimization problems in artificial intelligence (AI). It is one of the most popular fields of study among AI researchers. This book starts off by introducing you to reinforcement learning and Q-learning, in addition to helping you get familiar with OpenAI Gym as well as libraries such as Keras and TensorFlow. A few chapters into the book, you will gain insights into modelfree Q-learning and use deep Q-networks and double deep Q-networks to solve complex problems. This book will guide you in exploring use cases such as self-driving vehicles and OpenAI Gym’s CartPole problem. You will also learn how to tune and optimize Q-networks and their hyperparameters. As you progress, you will understand the reinforcement learning approach to solving real-world problems. You will also explore how to use Q-learning and related algorithms in real-world applications such as scientific research. Toward the end, you’ll gain a sense of what’s in store for reinforcement learning. By the end of this book, you will be equipped with the skills you need to solve reinforcement learning problems using Q-learning algorithms with OpenAI Gym, Keras, and TensorFlow. What you will learnExplore the fundamentals of reinforcement learning and the state-action-reward processUnderstand Markov decision processesGet well versed with libraries such as Keras, and TensorFlowCreate and deploy model-free learning and deep Q-learning agents with TensorFlow, Keras, and OpenAI GymChoose and optimize a Q-Network’s learning parameters and fine-tune its performanceDiscover real-world applications and use cases of Q-learningWho this book is for If you are a machine learning developer, engineer, or professional who wants to delve into the deep learning approach for a complex environment, then this is the book for you. Proficiency in Python programming and basic understanding of decision-making in reinforcement learning is assumed.

Hands-On Ensemble Learning with Python

Author : George Kyriakides
Publisher : Packt Publishing Ltd
ISBN 13 : 178961788X
Total Pages : 284 pages
Book Rating : 4.7/5 (896 download)

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Book Synopsis Hands-On Ensemble Learning with Python by : George Kyriakides

Download or read book Hands-On Ensemble Learning with Python written by George Kyriakides and published by Packt Publishing Ltd. This book was released on 2019-07-19 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: Combine popular machine learning techniques to create ensemble models using Python Key FeaturesImplement ensemble models using algorithms such as random forests and AdaBoostApply boosting, bagging, and stacking ensemble methods to improve the prediction accuracy of your model Explore real-world data sets and practical examples coded in scikit-learn and KerasBook Description Ensembling is a technique of combining two or more similar or dissimilar machine learning algorithms to create a model that delivers superior predictive power. This book will demonstrate how you can use a variety of weak algorithms to make a strong predictive model. With its hands-on approach, you'll not only get up to speed on the basic theory but also the application of various ensemble learning techniques. Using examples and real-world datasets, you'll be able to produce better machine learning models to solve supervised learning problems such as classification and regression. Furthermore, you'll go on to leverage ensemble learning techniques such as clustering to produce unsupervised machine learning models. As you progress, the chapters will cover different machine learning algorithms that are widely used in the practical world to make predictions and classifications. You'll even get to grips with the use of Python libraries such as scikit-learn and Keras for implementing different ensemble models. By the end of this book, you will be well-versed in ensemble learning, and have the skills you need to understand which ensemble method is required for which problem, and successfully implement them in real-world scenarios. What you will learnImplement ensemble methods to generate models with high accuracyOvercome challenges such as bias and varianceExplore machine learning algorithms to evaluate model performanceUnderstand how to construct, evaluate, and apply ensemble modelsAnalyze tweets in real time using Twitter's streaming APIUse Keras to build an ensemble of neural networks for the MovieLens datasetWho this book is for This book is for data analysts, data scientists, machine learning engineers and other professionals who are looking to generate advanced models using ensemble techniques. An understanding of Python code and basic knowledge of statistics is required to make the most out of this book.

Hands-On Data Preprocessing in Python

Author : Roy Jafari
Publisher : Packt Publishing Ltd
ISBN 13 : 1801079951
Total Pages : 602 pages
Book Rating : 4.8/5 (1 download)

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Book Synopsis Hands-On Data Preprocessing in Python by : Roy Jafari

Download or read book Hands-On Data Preprocessing in Python written by Roy Jafari and published by Packt Publishing Ltd. This book was released on 2022-01-21 with total page 602 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get your raw data cleaned up and ready for processing to design better data analytic solutions Key FeaturesDevelop the skills to perform data cleaning, data integration, data reduction, and data transformationMake the most of your raw data with powerful data transformation and massaging techniquesPerform thorough data cleaning, including dealing with missing values and outliersBook Description Hands-On Data Preprocessing is a primer on the best data cleaning and preprocessing techniques, written by an expert who's developed college-level courses on data preprocessing and related subjects. With this book, you'll be equipped with the optimum data preprocessing techniques from multiple perspectives, ensuring that you get the best possible insights from your data. You'll learn about different technical and analytical aspects of data preprocessing – data collection, data cleaning, data integration, data reduction, and data transformation – and get to grips with implementing them using the open source Python programming environment. The hands-on examples and easy-to-follow chapters will help you gain a comprehensive articulation of data preprocessing, its whys and hows, and identify opportunities where data analytics could lead to more effective decision making. As you progress through the chapters, you'll also understand the role of data management systems and technologies for effective analytics and how to use APIs to pull data. By the end of this Python data preprocessing book, you'll be able to use Python to read, manipulate, and analyze data; perform data cleaning, integration, reduction, and transformation techniques, and handle outliers or missing values to effectively prepare data for analytic tools. What you will learnUse Python to perform analytics functions on your dataUnderstand the role of databases and how to effectively pull data from databasesPerform data preprocessing steps defined by your analytics goalsRecognize and resolve data integration challengesIdentify the need for data reduction and execute itDetect opportunities to improve analytics with data transformationWho this book is for This book is for junior and senior data analysts, business intelligence professionals, engineering undergraduates, and data enthusiasts looking to perform preprocessing and data cleaning on large amounts of data. You don't need any prior experience with data preprocessing to get started with this book. However, basic programming skills, such as working with variables, conditionals, and loops, along with beginner-level knowledge of Python and simple analytics experience, are a prerequisite.