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Author: Mitch Garnaat
Publisher: "O'Reilly Media, Inc."
ISBN: 144930544X
Category : Computers
Languages : en
Pages : 75
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Book Description
This book focuses on Elastic Compute Cloud (EC2) and Simple Storage Service (S3) for developers writing in Python.
Author: Mitch Garnaat
Publisher: "O'Reilly Media, Inc."
ISBN: 144930544X
Category : Computers
Languages : en
Pages : 75
Get Book Here
Book Description
This book focuses on Elastic Compute Cloud (EC2) and Simple Storage Service (S3) for developers writing in Python.
Author: Mitch Garnaat
Publisher: "O'Reilly Media, Inc."
ISBN: 1449320481
Category : Computers
Languages : en
Pages : 75
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Book Description
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
Author: John Culkin
Publisher: "O'Reilly Media, Inc."
ISBN: 1492092576
Category : Computers
Languages : en
Pages : 355
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Book Description
This practical guide provides over 100 self-contained recipes to help you creatively solve issues you may encounter in your AWS cloud endeavors. If you're comfortable with rudimentary scripting and general cloud concepts, this cookbook will give you what you need to both address foundational tasks and create high-level capabilities. AWS Cookbook provides real-world examples that incorporate best practices. Each recipe includes code that you can safely execute in a sandbox AWS account to ensure that it works. From there, you can customize the code to help construct your application or fix your specific existing problem. Recipes also include a discussion that explains the approach and provides context. This cookbook takes you beyond theory, providing the nuts and bolts you need to successfully build on AWS. You'll find recipes for: Organizing multiple accounts for enterprise deployments Locking down S3 buckets Analyzing IAM roles Autoscaling a containerized service Summarizing news articles Standing up a virtual call center Creating a chatbot that can pull answers from a knowledge repository Automating security group rule monitoring, looking for rogue traffic flows And more.
Author: Chris Albon
Publisher: "O'Reilly Media, Inc."
ISBN: 1491989335
Category : Computers
Languages : en
Pages : 285
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Book Description
This practical guide provides nearly 200 self-contained recipes to help you solve machine learning challenges you may encounter in your daily work. If you’re comfortable with Python and its libraries, including pandas and scikit-learn, you’ll be able to address specific problems such as loading data, handling text or numerical data, model selection, and dimensionality reduction and many other topics. Each recipe includes code that you can copy and paste into a toy dataset to ensure that it actually works. From there, you can insert, combine, or adapt the code to help construct your application. Recipes also include a discussion that explains the solution and provides meaningful context. This cookbook takes you beyond theory and concepts by providing the nuts and bolts you need to construct working machine learning applications. You’ll find recipes for: Vectors, matrices, and arrays Handling numerical and categorical data, text, images, and dates and times Dimensionality reduction using feature extraction or feature selection Model evaluation and selection Linear and logical regression, trees and forests, and k-nearest neighbors Support vector machines (SVM), naïve Bayes, clustering, and neural networks Saving and loading trained models
Author: Alex Martelli
Publisher: "O'Reilly Media, Inc."
ISBN: 0596554745
Category : Computers
Languages : en
Pages : 847
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Book Description
Portable, powerful, and a breeze to use, Python is the popular open source object-oriented programming language used for both standalone programs and scripting applications. It is now being used by an increasing number of major organizations, including NASA and Google.Updated for Python 2.4, The Python Cookbook, 2nd Edition offers a wealth of useful code for all Python programmers, not just advanced practitioners. Like its predecessor, the new edition provides solutions to problems that Python programmers face everyday.It now includes over 200 recipes that range from simple tasks, such as working with dictionaries and list comprehensions, to complex tasks, such as monitoring a network and building a templating system. This revised version also includes new chapters on topics such as time, money, and metaprogramming.Here's a list of additional topics covered: Manipulating text Searching and sorting Working with files and the filesystem Object-oriented programming Dealing with threads and processes System administration Interacting with databases Creating user interfaces Network and web programming Processing XML Distributed programming Debugging and testing Another advantage of The Python Cookbook, 2nd Edition is its trio of authors--three well-known Python programming experts, who are highly visible on email lists and in newsgroups, and speak often at Python conferences.With scores of practical examples and pertinent background information, The Python Cookbook, 2nd Edition is the one source you need if you're looking to build efficient, flexible, scalable, and well-integrated systems.
Author: Lucas Chan
Publisher: Packt Publishing Ltd
ISBN: 1787121526
Category : Computers
Languages : en
Pages : 383
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Book Description
Build, automate, and manage your AWS-based cloud environments About This Book Install, configure, and administer computing, storage, and networking in the AWS cloud Automate your infrastructure and control every aspect of it through infrastructure as code Work through exciting recipes to administer your AWS cloud Who This Book Is For If you are an administrator, DevOps engineer, or an IT professional who is moving to an AWS-based cloud environment, then this book is for you. It assumes familiarity with cloud computing platforms, and that you have some understanding of virtualization, networking, and other administration-related tasks. What You Will Learn Discover the best practices to achieve an automated repeatable infrastructure in AWS Bring down your IT costs by managing AWS successfully and deliver high availability, fault tolerance, and scalability Make any website faster with static and dynamic caching Create monitoring and alerting dashboards using CloudWatch Migrate a database to AWS Set up consolidated billing to achieve simple and effective cost management with accounts Host a domain and find out how you can automate health checks In Detail Amazon Web Services (AWS) is a bundled remote computing service that provides cloud computing infrastructure over the Internet with storage, bandwidth, and customized support for application programming interfaces (API). Implementing these services to efficiently administer your cloud environments is a core task. This book will help you build and administer your cloud environment with AWS. We'll begin with the AWS fundamentals, and you'll build the foundation for the recipes you'll work on throughout the book. Next, you will find out how to manage multiple accounts and set up consolidated billing. You will then learn to set up reliable and fast hosting for static websites, share data between running instances, and back up your data for compliance. Moving on, you will find out how to use the compute service to enable consistent and fast instance provisioning, and will see how to provision storage volumes and autoscale an application server. Next, you'll discover how to effectively use the networking and database service of AWS. You will also learn about the different management tools of AWS along with securing your AWS cloud. Finally, you will learn to estimate the costs for your cloud. By the end of the book, you will be able to easily administer your AWS cloud. Style and approach This practical guide is packed with clear, practical, instruction-based recipes that will enable you to use and implement the latest features of AWS.
Author: Michael Heydt
Publisher: Packt Publishing Ltd
ISBN: 1787286630
Category : Computers
Languages : en
Pages : 356
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Book Description
Untangle your web scraping complexities and access web data with ease using Python scripts Key Features Hands-on recipes for advancing your web scraping skills to expert level One-stop solution guide to address complex and challenging web scraping tasks using Python Understand web page structures and collect data from a website with ease Book Description Python Web Scraping Cookbook is a solution-focused book that will teach you techniques to develop high-performance Scrapers, and deal with cookies, hidden form fields, Ajax-based sites and proxies. You'll explore a number of real-world scenarios where every part of the development or product life cycle will be fully covered. You will not only develop the skills to design reliable, high-performing data flows, but also deploy your codebase to Amazon Web Services (AWS). If you are involved in software engineering, product development, or data mining or in building data-driven products, you will find this book useful as each recipe has a clear purpose and objective. Right from extracting data from websites to writing a sophisticated web crawler, the book's independent recipes will be extremely helpful while on the job. This book covers Python libraries, requests, and BeautifulSoup. You will learn about crawling, web spidering, working with AJAX websites, and paginated items. You will also understand to tackle problems such as 403 errors, working with proxy, scraping images, and LXML. By the end of this book, you will be able to scrape websites more efficiently and deploy and operate your scraper in the cloud. What you will learn Use a variety of tools to scrape any website and data, including Scrapy and Selenium Master expression languages, such as XPath and CSS, and regular expressions to extract web data Deal with scraping traps such as hidden form fields, throttling, pagination, and different status codes Build robust scraping pipelines with SQS and RabbitMQ Scrape assets like image media and learn what to do when Scraper fails to run Explore ETL techniques of building a customized crawler, parser, and convert structured and unstructured data from websites Deploy and run your scraper as a service in AWS Elastic Container Service Who this book is for This book is ideal for Python programmers, web administrators, security professionals, and anyone who wants to perform web analytics. Familiarity with Python and basic understanding of web scraping will be useful to make the best of this book.
Author: Jaime Buelta
Publisher: Packt Publishing Ltd
ISBN: 1800202598
Category : Computers
Languages : en
Pages : 527
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Book Description
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.
Author: Indra den Bakker
Publisher: Packt Publishing Ltd
ISBN: 1787122255
Category : Computers
Languages : en
Pages : 321
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Book Description
Solve different problems in modelling deep neural networks using Python, Tensorflow, and Keras with this practical guide About This Book Practical recipes on training different neural network models and tuning them for optimal performance Use Python frameworks like TensorFlow, Caffe, Keras, Theano for Natural Language Processing, Computer Vision, and more A hands-on guide covering the common as well as the not so common problems in deep learning using Python Who This Book Is For This book is intended for machine learning professionals who are looking to use deep learning algorithms to create real-world applications using Python. Thorough understanding of the machine learning concepts and Python libraries such as NumPy, SciPy and scikit-learn is expected. Additionally, basic knowledge in linear algebra and calculus is desired. What You Will Learn Implement different neural network models in Python Select the best Python framework for deep learning such as PyTorch, Tensorflow, MXNet and Keras Apply tips and tricks related to neural networks internals, to boost learning performances Consolidate machine learning principles and apply them in the deep learning field Reuse and adapt Python code snippets to everyday problems Evaluate the cost/benefits and performance implication of each discussed solution In Detail Deep Learning is revolutionizing a wide range of industries. For many applications, deep learning has proven to outperform humans by making faster and more accurate predictions. This book provides a top-down and bottom-up approach to demonstrate deep learning solutions to real-world problems in different areas. These applications include Computer Vision, Natural Language Processing, Time Series, and Robotics. The Python Deep Learning Cookbook presents technical solutions to the issues presented, along with a detailed explanation of the solutions. Furthermore, a discussion on corresponding pros and cons of implementing the proposed solution using one of the popular frameworks like TensorFlow, PyTorch, Keras and CNTK is provided. The book includes recipes that are related to the basic concepts of neural networks. All techniques s, as well as classical networks topologies. The main purpose of this book is to provide Python programmers a detailed list of recipes to apply deep learning to common and not-so-common scenarios. Style and approach Unique blend of independent recipes arranged in the most logical manner
Author: Joshua Arvin Lat
Publisher: Packt Publishing Ltd
ISBN: 1800566123
Category : Computers
Languages : en
Pages : 763
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Book Description
A step-by-step solution-based guide to preparing building, training, and deploying high-quality machine learning models with Amazon SageMaker Key FeaturesPerform ML experiments with built-in and custom algorithms in SageMakerExplore proven solutions when working with TensorFlow, PyTorch, Hugging Face Transformers, and scikit-learnUse the different features and capabilities of SageMaker to automate relevant ML processesBook Description Amazon SageMaker is a fully managed machine learning (ML) service that helps data scientists and ML practitioners manage ML experiments. In this book, you'll use the different capabilities and features of Amazon SageMaker to solve relevant data science and ML problems. This step-by-step guide features 80 proven recipes designed to give you the hands-on machine learning experience needed to contribute to real-world experiments and projects. You'll cover the algorithms and techniques that are commonly used when training and deploying NLP, time series forecasting, and computer vision models to solve ML problems. You'll explore various solutions for working with deep learning libraries and frameworks such as TensorFlow, PyTorch, and Hugging Face Transformers in Amazon SageMaker. You'll also learn how to use SageMaker Clarify, SageMaker Model Monitor, SageMaker Debugger, and SageMaker Experiments to debug, manage, and monitor multiple ML experiments and deployments. Moreover, you'll have a better understanding of how SageMaker Feature Store, Autopilot, and Pipelines can meet the specific needs of data science teams. By the end of this book, you'll be able to combine the different solutions you've learned as building blocks to solve real-world ML problems. What you will learnTrain and deploy NLP, time series forecasting, and computer vision models to solve different business problemsPush the limits of customization in SageMaker using custom container imagesUse AutoML capabilities with SageMaker Autopilot to create high-quality modelsWork with effective data analysis and preparation techniquesExplore solutions for debugging and managing ML experiments and deploymentsDeal with bias detection and ML explainability requirements using SageMaker ClarifyAutomate intermediate and complex deployments and workflows using a variety of solutionsWho this book is for This book is for developers, data scientists, and machine learning practitioners interested in using Amazon SageMaker to build, analyze, and deploy machine learning models with 80 step-by-step recipes. All you need is an AWS account to get things running. Prior knowledge of AWS, machine learning, and the Python programming language will help you to grasp the concepts covered in this book more effectively.
