Serverless Deep Learning With Tensorflow And Aws Lambda

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Hands On Serverless Deep Learning With Tensorflow And Aws Lambda

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Author : Rustem Feyzkhanov
language : en
Publisher: Impackt Publishing
Release Date : 2019-01-31

Hands On Serverless Deep Learning With Tensorflow And Aws Lambda written by Rustem Feyzkhanov and has been published by Impackt Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-31 with categories.

Use the serverless computing approach to save time and money Key Features Save your time by deploying deep learning models with ease using the AWS serverless infrastructure Get a solid grip on AWS services and use them with TensorFlow for efficient deep learning Includes tips, tricks and best practices on serverless deep learning that you can use in a production environment Book Description One of the main problems with deep learning models is finding the right way to deploy them within the company's IT infrastructure. Serverless architecture changes the rules of the game--instead of thinking about cluster management, scalability, and query processing, it allows us to focus specifically on training the model. This book prepares you to use your own custom-trained models with AWS Lambda to achieve a simplified serverless computing approach without spending much time and money. You will use AWS Services to deploy TensorFlow models without spending hours training and deploying them. You'll learn to deploy with serverless infrastructures, create APIs, process pipelines, and more with the tips included in this book. By the end of the book, you will have implemented your own project that demonstrates how to use AWS Lambda effectively so as to serve your TensorFlow models in the best possible way. What you will learn Gain practical experience by working hands-on with serverless infrastructures (AWS Lambda) Export and deploy deep learning models using Tensorflow Build a solid base in AWS and its various functions Create a deep learning API using AWS Lambda Look at the AWS API gateway Create deep learning processing pipelines using AWS functions Create deep learning production pipelines using AWS Lambda and AWS Step Function Who this book is for This book will benefit data scientists who want to learn how to deploy models easily and beginners who want to learn about deploying into the cloud. No prior knowledge of TensorFlow or AWS is required.

Serverless Deep Learning With Tensorflow And Aws Lambda

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Author : Rustem Feyzkhanov
language : en
Publisher:
Release Date : 2018

Serverless Deep Learning With Tensorflow And Aws Lambda written by Rustem Feyzkhanov and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.

"One of the main problems with deep learning models is finding the right way to deploy them within the company's IT infrastructure. Serverless architecture changes the rules of the game ... it allows us to focus specifically on training the model. This course prepares you to use your own custom-trained models with AWS Lambda to achieve a simplified serverless computing approach without spending much time and money."--Resource description page.

Machine Learning Bookcamp

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Author : Alexey Grigorev
language : en
Publisher: Simon and Schuster
Release Date : 2021-11-23

Machine Learning Bookcamp written by Alexey Grigorev and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-23 with Computers categories.

Master key machine learning concepts as you build actual projects! Machine learning is what you need for analyzing customer behavior, predicting price trends, evaluating risk, and much more. To master ML, you need great examples, clear explanations, and lots of practice. This book delivers all three! Machine learning bookcamp presents realistic, practical machine learning scenarios, along with crystal-clear coverage of key concepts. In it, you'll complete engaging projects, such as creating a car price predictor using linear regression and deploying a churn prediction service. You'll go beyond the algorithms and explore important techniques like deploying ML applications on serverless systems and serving models with Kubernetes and Kubeflow. Dig in, get your hands dirty, and have fun building your ML skills!

Machine Learning Engineering On Aws

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Author : Joshua Arvin Lat
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-10-27

Machine Learning Engineering On Aws written by Joshua Arvin Lat and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-27 with Computers categories.

Work seamlessly with production-ready machine learning systems and pipelines on AWS by addressing key pain points encountered in the ML life cycle Key FeaturesGain practical knowledge of managing ML workloads on AWS using Amazon SageMaker, Amazon EKS, and moreUse container and serverless services to solve a variety of ML engineering requirementsDesign, build, and secure automated MLOps pipelines and workflows on AWSBook Description There is a growing need for professionals with experience in working on machine learning (ML) engineering requirements as well as those with knowledge of automating complex MLOps pipelines in the cloud. This book explores a variety of AWS services, such as Amazon Elastic Kubernetes Service, AWS Glue, AWS Lambda, Amazon Redshift, and AWS Lake Formation, which ML practitioners can leverage to meet various data engineering and ML engineering requirements in production. This machine learning book covers the essential concepts as well as step-by-step instructions that are designed to help you get a solid understanding of how to manage and secure ML workloads in the cloud. As you progress through the chapters, you'll discover how to use several container and serverless solutions when training and deploying TensorFlow and PyTorch deep learning models on AWS. You'll also delve into proven cost optimization techniques as well as data privacy and model privacy preservation strategies in detail as you explore best practices when using each AWS. By the end of this AWS book, you'll be able to build, scale, and secure your own ML systems and pipelines, which will give you the experience and confidence needed to architect custom solutions using a variety of AWS services for ML engineering requirements. What you will learnFind out how to train and deploy TensorFlow and PyTorch models on AWSUse containers and serverless services for ML engineering requirementsDiscover how to set up a serverless data warehouse and data lake on AWSBuild automated end-to-end MLOps pipelines using a variety of servicesUse AWS Glue DataBrew and SageMaker Data Wrangler for data engineeringExplore different solutions for deploying deep learning models on AWSApply cost optimization techniques to ML environments and systemsPreserve data privacy and model privacy using a variety of techniquesWho this book is for This book is for machine learning engineers, data scientists, and AWS cloud engineers interested in working on production data engineering, machine learning engineering, and MLOps requirements using a variety of AWS services such as Amazon EC2, Amazon Elastic Kubernetes Service (EKS), Amazon SageMaker, AWS Glue, Amazon Redshift, AWS Lake Formation, and AWS Lambda -- all you need is an AWS account to get started. Prior knowledge of AWS, machine learning, and the Python programming language will help you to grasp the concepts covered in this book more effectively.

Machine Learning Engineering On Aws

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Author : Joshua Arvin Lat
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-10-27

Machine Learning Engineering On Aws written by Joshua Arvin Lat and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-27 with Computers categories.

Work seamlessly with production-ready machine learning systems and pipelines on AWS by addressing key pain points encountered in the ML life cycle Key FeaturesGain practical knowledge of managing ML workloads on AWS using Amazon SageMaker, Amazon EKS, and moreUse container and serverless services to solve a variety of ML engineering requirementsDesign, build, and secure automated MLOps pipelines and workflows on AWSBook Description There is a growing need for professionals with experience in working on machine learning (ML) engineering requirements as well as those with knowledge of automating complex MLOps pipelines in the cloud. This book explores a variety of AWS services, such as Amazon Elastic Kubernetes Service, AWS Glue, AWS Lambda, Amazon Redshift, and AWS Lake Formation, which ML practitioners can leverage to meet various data engineering and ML engineering requirements in production. This machine learning book covers the essential concepts as well as step-by-step instructions that are designed to help you get a solid understanding of how to manage and secure ML workloads in the cloud. As you progress through the chapters, you'll discover how to use several container and serverless solutions when training and deploying TensorFlow and PyTorch deep learning models on AWS. You'll also delve into proven cost optimization techniques as well as data privacy and model privacy preservation strategies in detail as you explore best practices when using each AWS. By the end of this AWS book, you'll be able to build, scale, and secure your own ML systems and pipelines, which will give you the experience and confidence needed to architect custom solutions using a variety of AWS services for ML engineering requirements. What you will learnFind out how to train and deploy TensorFlow and PyTorch models on AWSUse containers and serverless services for ML engineering requirementsDiscover how to set up a serverless data warehouse and data lake on AWSBuild automated end-to-end MLOps pipelines using a variety of servicesUse AWS Glue DataBrew and SageMaker Data Wrangler for data engineeringExplore different solutions for deploying deep learning models on AWSApply cost optimization techniques to ML environments and systemsPreserve data privacy and model privacy using a variety of techniquesWho this book is for This book is for machine learning engineers, data scientists, and AWS cloud engineers interested in working on production data engineering, machine learning engineering, and MLOps requirements using a variety of AWS services such as Amazon EC2, Amazon Elastic Kubernetes Service (EKS), Amazon SageMaker, AWS Glue, Amazon Redshift, AWS Lake Formation, and AWS Lambda -- all you need is an AWS account to get started. Prior knowledge of AWS, machine learning, and the Python programming language will help you to grasp the concepts covered in this book more effectively.

Ai As A Service

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Author : Peter Elger
language : en
Publisher: Manning
Release Date : 2020-10-06

Ai As A Service written by Peter Elger and has been published by Manning this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-06 with Computers categories.

AI as a Service is a practical handbook to building and implementing serverless AI applications, without bogging you down with a lot of theory. Instead, you’ll find easy-to-digest instruction and two complete hands-on serverless AI builds in this must-have guide! Summary Companies everywhere are moving everyday business processes over to the cloud, and AI is increasingly being given the reins in these tasks. As this massive digital transformation continues, the combination of serverless computing and AI promises to become the de facto standard for business-to-consumer platform development—and developers who can design, develop, implement, and maintain these systems will be in high demand! AI as a Service is a practical handbook to building and implementing serverless AI applications, without bogging you down with a lot of theory. Instead, you’ll find easy-to-digest instruction and two complete hands-on serverless AI builds in this must-have guide! Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Cloud-based AI services can automate a variety of labor intensive business tasks in areas such as customer service, data analysis, and financial reporting. The secret is taking advantage of pre-built tools like Amazon Rekognition for image analysis or AWS Comprehend for natural language processing. That way, there’s no need to build expensive custom software. Artificial Intelligence (AI), a machine’s ability to learn and make predictions based on patterns it identifies, is already being leveraged by businesses around the world in areas like targeted product recommendations, financial forecasting and resource planning, customer service chatbots, healthcare diagnostics, data security, and more. With the exciting combination of serverless computing and AI, software developers now have enormous power to improve their businesses’ existing systems and rapidly deploy new AI-enabled platforms. And to get on this fast-moving train, you don’t have to invest loads of time and effort in becoming a data scientist or AI expert, thanks to cloud platforms and the readily available off-the-shelf cloud-based AI services! About the book AI as a Service is a fast-paced guide to harnessing the power of cloud-based solutions. You’ll learn to build real-world apps—such as chatbots and text-to-speech services—by stitching together cloud components. Work your way from small projects to large data-intensive applications. What's inside - Apply cloud AI services to existing platforms - Design and build scalable data pipelines - Debug and troubleshoot AI services - Start fast with serverless templates About the reader For software developers familiar with cloud basics. About the author Peter Elger and Eóin Shanaghy are founders and CEO/CTO of fourTheorem, a software solutions company providing expertise on architecture, DevOps, and machine learning. Table of Contents PART 1 - FIRST STEPS 1 A tale of two technologies 2 Building a serverless image recognition system, part 1 3 Building a serverless image recognition system, part 2 PART 2 - TOOLS OF THE TRADE 4 Building and securing a web application the serverless way 5 Adding AI interfaces to a web application 6 How to be effective with AI as a Service 7 Applying AI to existing platforms PART 3 - BRINGING IT ALL TOGETHER 8 Gathering data at scale for real-world AI 9 Extracting value from large data sets with AI

Building Serverless Applications With Python

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Author : Jalem Raj Rohit
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-04-20

Building Serverless Applications With Python written by Jalem Raj Rohit and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-20 with Computers categories.

Building efficient Python applications at minimal cost by adopting serverless architectures Key Features Design and set up a data flow between cloud services and custom business logic Make your applications efficient and reliable using serverless architecture Build and deploy scalable serverless Python APIs Book Description Serverless architectures allow you to build and run applications and services without having to manage the infrastructure. Many companies have adopted this architecture to save cost and improve scalability. This book will help you design serverless architectures for your applications with AWS and Python. The book is divided into three modules. The first module explains the fundamentals of serverless architecture and how AWS lambda functions work. In the next module, you will learn to build, release, and deploy your application to production. You will also learn to log and test your application. In the third module, we will take you through advanced topics such as building a serverless API for your application. You will also learn to troubleshoot and monitor your app and master AWS lambda programming concepts with API references. Moving on, you will also learn how to scale up serverless applications and handle distributed serverless systems in production. By the end of the book, you will be equipped with the knowledge required to build scalable and cost-efficient Python applications with a serverless framework. What you will learn Understand how AWS Lambda and Microsoft Azure Functions work and use them to create an application Explore various triggers and how to select them, based on the problem statement Build deployment packages for Lambda functions Master the finer details about building Lambda functions and versioning Log and monitor serverless applications Learn about security in AWS and Lambda functions Scale up serverless applications to handle huge workloads and serverless distributed systems in production Understand SAM model deployment in AWS Lambda Who this book is for This book is for Python developers who would like to learn about serverless architecture. Python programming knowledge is assumed.

Mastering Serverless A Deep Dive Into Aws Lambda

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Author : Peter Jones
language : en
Publisher: Walzone Press
Release Date : 2025-01-17

Mastering Serverless A Deep Dive Into Aws Lambda written by Peter Jones and has been published by Walzone Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-17 with Computers categories.

"Mastering Serverless: A Deep Dive into AWS Lambda" offers an exhaustive exploration of the groundbreaking realm of serverless computing, emphasizing AWS Lambda, Amazon Web Services' premier serverless computing service. As serverless architecture emerges as a pivotal trend in software development, this book stands as an essential resource for software developers, architects, and IT professionals eager to leverage the power of serverless technology. Beginning with the setup of your development environment and continuing through the design of serverless applications, performance optimization, and the implementation of advanced architectural patterns, this guide addresses every critical facet of serverless computing. Each chapter is meticulously structured to deliver comprehensive knowledge, practical examples, and best practices, enabling readers to craft efficient, secure, and scalable serverless applications. Whether you are a novice keen to delve into serverless computing or an experienced developer seeking to refine your skills in AWS Lambda, this book provides actionable insights and clear explanations to help you navigate the intricacies of serverless architectures. Unlock the potential of serverless computing, reduce operational costs, and accelerate your application development with "Mastering Serverless: A Deep Dive into AWS Lambda." Immerse yourself in the future of computing and revolutionize the way you build applications in the cloud.

Aws Lambda Quick Start Guide

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Author : Markus Klems
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-06-29

Aws Lambda Quick Start Guide written by Markus Klems and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-29 with Computers categories.

Discover techniques and tools for building serverless applications with AWS Lambda Key Features Learn to write, run, and deploy Lambda functions in the AWS cloud Make the most of AWS Lambda functions to build scalable and cost-efficient systems A practical guide to developing serverless services and applications in Node.js, Java, Python, and C# Book Description AWS Lambda is a part of AWS that lets you run your code without provisioning or managing servers. This enables you to deploy applications and backend services that operate with no upfront cost. This book gets you up to speed on how to build scalable systems and deploy serverless applications with AWS Lambda. The book starts with the fundamental concepts of AWS Lambda, and then teaches you how to combine your applications with other AWS services, such as AmazonAPI Gateway and DynamoDB. This book will also give a quick walk through on how to use the Serverless Framework to build larger applications that can structure code or autogenerate boilerplate code that can be used to get started quickly for increased productivity. Toward the end of the book, you will learn how to write, run, and test Lambda functions using Node.js, Java, Python, and C#. What you will learn Understand the fundamental concepts of AWS Lambda Get to grips with the Serverless Framework and how to create a serverless project Testing and debugging Lambda functions Create a stateful, serverless backend with DynamoDB Program AWS Lambda with Java, Python, and C# Program a lambda function with Node.js Who this book is for This book is primarily for IT architects and developers who want to build scalable systems and deploy serverless applications with AWS Lambda. No prior knowledge of AWS is necessary.

Hands On Serverless Computing

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Author : Kuldeep Chowhan
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-07-23

Hands On Serverless Computing written by Kuldeep Chowhan and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-23 with Computers categories.

Deploy functions efficiently using different cloud-based serverless offerings Key Features Understand the concept of Function-as-a-Service Implement Serverless solutions using AWS Lambda, Azure Functions and Google Cloud Functions Practical approach towards choosing the best tool for your serverless environment Book Description Serverless applications and architectures are gaining momentum and are increasingly being used by companies of all sizes. Serverless software takes care of many problems that developers face when running systems and servers, such as fault tolerance, centralized logging, horizontal scalability, and deployments. You will learn how to harness serverless technology to rapidly reduce production time and minimize your costs, while still having the freedom to customize your code, without hindering functionality. Upon finishing the book, you will have the knowledge and resources to build your own serverless application hosted in AWS, Microsoft Azure, or Google Cloud Platform, and will have experienced the benefits of event-driven technology for yourself. This hands-on guide dives into the basis of serverless architectures and how to build them using Node.js as a programming language, Visual Studio Code for code editing, and Postman for quickly and securely developing applications without the hassle of configuring and maintaining infrastructure on three public cloud platforms. What you will learn Understand the benefts of serverless computing and know when to use it Develop serverless applications on AWS, Azure, and Google Cloud Get to grips with Function as a Service (FaaS) Apply triggers to serverless functions Build event-driven apps using serverless frameworks Use the Node.js programming language to build serverless apps Use code editors, such as Visual Studio Code, as development environments Master the best development practices for creating scalable and practical solutions Who this book is for This book is targeted towards developers, system administrators or any stakeholder working in the Serverless environment and want to understand how functions work. Basic idea of serverless architecture can be an added advantage