Hands On Enterprise Automation With Python

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Hands-On Enterprise Automation with Python

Author : Bassem Aly
Publisher : Packt Publishing Ltd
Page : 383 pages
File Size : 42,6 Mb
Release : 2018-06-28
Category : Computers
ISBN : 9781788992640

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Hands-On Enterprise Automation with Python by Bassem Aly Pdf

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
Page : 362 pages
File Size : 50,5 Mb
Release : 2018-12-28
Category : Computers
ISBN : 9781789530636

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Hands-On Enterprise Application Development with Python by Saurabh Badhwar Pdf

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
Page : 736 pages
File Size : 50,7 Mb
Release : 2018-10-26
Category : Computers
ISBN : 9781788621359

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Hands-On Software Engineering with Python by Brian Allbee Pdf

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.

Automate the Boring Stuff with Python, 2nd Edition

Author : Al Sweigart
Publisher : No Starch Press
Page : 593 pages
File Size : 50,8 Mb
Release : 2019-11-12
Category : Computers
ISBN : 9781593279936

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Automate the Boring Stuff with Python, 2nd Edition by Al Sweigart Pdf

Learn how to code while you write programs that effortlessly perform useful feats of automation! The second edition of this international fan favorite includes a brand-new chapter on input validation, Gmail and Google Sheets automations, tips for updating CSV files, and more. If you've ever spent hours renaming files or updating spreadsheet cells, you know how tedious tasks like these can be. But what if you could have your computer do them for you? Automate the Boring Stuff with Python, 2nd Edition teaches even the technically uninclined how to write programs that do in minutes what would take hours to do by hand—no prior coding experience required! This new, fully revised edition of Al Sweigart’s bestselling Pythonic classic, Automate the Boring Stuff with Python, covers all the basics of Python 3 while exploring its rich library of modules for performing specific tasks, like scraping data off the Web, filling out forms, renaming files, organizing folders, sending email responses, and merging, splitting, or encrypting PDFs. There’s also a brand-new chapter on input validation, tutorials on automating Gmail and Google Sheets, tips on automatically updating CSV files, and other recent feats of automations that improve your efficiency. Detailed, step-by-step instructions walk you through each program, allowing you to create useful tools as you build out your programming skills, and updated practice projects at the end of each chapter challenge you to improve those programs and use your newfound skills to automate similar tasks. Boring tasks no longer have to take to get through—and neither does learning Python!

pytest Quick Start Guide

Author : Bruno Oliveira
Publisher : Packt Publishing Ltd
Page : 153 pages
File Size : 49,9 Mb
Release : 2018-08-29
Category : Computers
ISBN : 9781789343823

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pytest Quick Start Guide by Bruno Oliveira Pdf

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
Page : 527 pages
File Size : 55,5 Mb
Release : 2020-05-29
Category : Computers
ISBN : 9781800202597

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Python Automation Cookbook by Jaime Buelta Pdf

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 Reactive Programming with Python

Author : Romain Picard
Publisher : Packt Publishing Ltd
Page : 411 pages
File Size : 45,8 Mb
Release : 2018-10-25
Category : Computers
ISBN : 9781789132755

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Hands-On Reactive Programming with Python by Romain Picard Pdf

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 Q-Learning with Python

Author : Nazia Habib
Publisher : Packt Publishing Ltd
Page : 200 pages
File Size : 50,6 Mb
Release : 2019-04-19
Category : Mathematics
ISBN : 9781789345759

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Hands-On Q-Learning with Python by Nazia Habib Pdf

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 Predictive Analytics with Python

Author : Alvaro Fuentes
Publisher : Packt Publishing Ltd
Page : 320 pages
File Size : 44,7 Mb
Release : 2018-12-28
Category : Computers
ISBN : 9781789134544

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Hands-On Predictive Analytics with Python by Alvaro Fuentes Pdf

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 Recommendation Systems with Python

Author : Rounak Banik
Publisher : Packt Publishing Ltd
Page : 141 pages
File Size : 50,9 Mb
Release : 2018-07-31
Category : Computers
ISBN : 9781788992534

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Hands-On Recommendation Systems with Python by Rounak Banik Pdf

With Hands-On Recommendation Systems with Python, learn the tools and techniques required in building various kinds of powerful recommendation systems (collaborative, knowledge and content based) and deploying them to the web Key Features Build industry-standard recommender systems Only familiarity with Python is required No need to wade through complicated machine learning theory to use this book Book Description Recommendation systems are at the heart of almost every internet business today; from Facebook to Netflix to Amazon. Providing good recommendations, whether it's friends, movies, or groceries, goes a long way in defining user experience and enticing your customers to use your platform. This book shows you how to do just that. You will learn about the different kinds of recommenders used in the industry and see how to build them from scratch using Python. No need to wade through tons of machine learning theory—you'll get started with building and learning about recommenders as quickly as possible.. In this book, you will build an IMDB Top 250 clone, a content-based engine that works on movie metadata. You'll use collaborative filters to make use of customer behavior data, and a Hybrid Recommender that incorporates content based and collaborative filtering techniques With this book, all you need to get started with building recommendation systems is a familiarity with Python, and by the time you're fnished, you will have a great grasp of how recommenders work and be in a strong position to apply the techniques that you will learn to your own problem domains. What you will learn Get to grips with the different kinds of recommender systems Master data-wrangling techniques using the pandas library Building an IMDB Top 250 Clone Build a content based engine to recommend movies based on movie metadata Employ data-mining techniques used in building recommenders Build industry-standard collaborative filters using powerful algorithms Building Hybrid Recommenders that incorporate content based and collaborative fltering Who this book is for If you are a Python developer and want to develop applications for social networking, news personalization or smart advertising, this is the book for you. Basic knowledge of machine learning techniques will be helpful, but not mandatory.

Hands-On Data Preprocessing in Python

Author : Roy Jafari
Publisher : Packt Publishing Ltd
Page : 602 pages
File Size : 41,9 Mb
Release : 2022-01-21
Category : Computers
ISBN : 9781801079952

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Hands-On Data Preprocessing in Python by Roy Jafari Pdf

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.

Network Programmability and Automation

Author : Jason Edelman,Scott S. Lowe,Matt Oswalt
Publisher : "O'Reilly Media, Inc."
Page : 842 pages
File Size : 44,7 Mb
Release : 2018-02-02
Category : Computers
ISBN : 9781491931318

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Network Programmability and Automation by Jason Edelman,Scott S. Lowe,Matt Oswalt Pdf

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 Ensemble Learning with Python

Author : George Kyriakides,Konstantinos G. Margaritis
Publisher : Packt Publishing Ltd
Page : 284 pages
File Size : 44,7 Mb
Release : 2019-07-19
Category : Computers
ISBN : 9781789617887

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Hands-On Ensemble Learning with Python by George Kyriakides,Konstantinos G. Margaritis Pdf

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 Transfer Learning with Python

Author : Dipanjan Sarkar,Raghav Bali,Tamoghna Ghosh
Publisher : Packt Publishing Ltd
Page : 430 pages
File Size : 40,9 Mb
Release : 2018-08-31
Category : Computers
ISBN : 9781788839051

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Hands-On Transfer Learning with Python by Dipanjan Sarkar,Raghav Bali,Tamoghna Ghosh Pdf

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.

Hands-On Data Structures and Algorithms with Python

Author : Dr. Basant Agarwal,Benjamin Baka
Publisher : Packt Publishing Ltd
Page : 389 pages
File Size : 44,8 Mb
Release : 2018-10-31
Category : Computers
ISBN : 9781788991933

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Hands-On Data Structures and Algorithms with Python by Dr. Basant Agarwal,Benjamin Baka Pdf

Learn to implement complex data structures and algorithms using Python Key FeaturesUnderstand the analysis and design of fundamental Python data structuresExplore advanced Python concepts such as Big O notation and dynamic programmingLearn functional and reactive implementations of traditional data structuresBook Description 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 sort algorithms in detail. By the end of the book, you will have learned how to build components that are easy to understand, debug, and use in different applications. You will get insights into Python implementation of all the important and relevant algorithms. What you will learnUnderstand object representation, attribute binding, and data encapsulationGain a solid understanding of Python data structures using algorithmsStudy algorithms using examples with pictorial representationLearn complex algorithms through easy explanation, implementing PythonBuild sophisticated and efficient data applications in PythonUnderstand common programming algorithms used in Python data scienceWrite efficient and robust code in Python 3.7Who this book is for This book is for developers who want to learn data structures and algorithms in Python to write complex and flexible programs. Basic Python programming knowledge is expected.