Scaling Python With Ray

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Scaling Python with Ray

Author : Holden Karau
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1098118766
Total Pages : 245 pages
Book Rating : 4.0/5 (981 download)

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Book Synopsis Scaling Python with Ray by : Holden Karau

Download or read book Scaling Python with Ray written by Holden Karau and published by "O'Reilly Media, Inc.". This book was released on 2022-11-29 with total page 245 pages. Available in PDF, EPUB and Kindle. Book excerpt: Serverless computing enables developers to concentrate solely on their applications rather than worry about where they've been deployed. With the Ray general-purpose serverless implementation in Python, programmers and data scientists can hide servers, implement stateful applications, support direct communication between tasks, and access hardware accelerators. In this book, experienced software architecture practitioners Holden Karau and Boris Lublinsky show you how to scale existing Python applications and pipelines, allowing you to stay in the Python ecosystem while reducing single points of failure and manual scheduling. Scaling Python with Ray is ideal for software architects and developers eager to explore successful case studies and learn more about decision and measurement effectiveness. If your data processing or server application has grown beyond what a single computer can handle, this book is for you. You'll explore distributed processing (the pure Python implementation of serverless) and learn how to: Implement stateful applications with Ray actors Build workflow management in Ray Use Ray as a unified system for batch and stream processing Apply advanced data processing with Ray Build microservices with Ray Implement reliable Ray applications

Learning Ray

Author : Max Pumperla
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1098117182
Total Pages : 277 pages
Book Rating : 4.0/5 (981 download)

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Book Synopsis Learning Ray by : Max Pumperla

Download or read book Learning Ray written by Max Pumperla and published by "O'Reilly Media, Inc.". This book was released on 2023-02-13 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get started with Ray, the open source distributed computing framework that simplifies the process of scaling compute-intensive Python workloads. With this practical book, Python programmers, data engineers, and data scientists will learn how to leverage Ray locally and spin up compute clusters. You'll be able to use Ray to structure and run machine learning programs at scale. Authors Max Pumperla, Edward Oakes, and Richard Liaw show you how to build machine learning applications with Ray. You'll understand how Ray fits into the current landscape of machine learning tools and discover how Ray continues to integrate ever more tightly with these tools. Distributed computation is hard, but by using Ray you'll find it easy to get started. Learn how to build your first distributed applications with Ray Core Conduct hyperparameter optimization with Ray Tune Use the Ray RLlib library for reinforcement learning Manage distributed training with the Ray Train library Use Ray to perform data processing with Ray Datasets Learn how work with Ray Clusters and serve models with Ray Serve Build end-to-end machine learning applications with Ray AIR

Scaling Python with Dask

Author : Holden Karau
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1098119835
Total Pages : 210 pages
Book Rating : 4.0/5 (981 download)

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Book Synopsis Scaling Python with Dask by : Holden Karau

Download or read book Scaling Python with Dask written by Holden Karau and published by "O'Reilly Media, Inc.". This book was released on 2023-07-19 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern systems contain multi-core CPUs and GPUs that have the potential for parallel computing. But many scientific Python tools were not designed to leverage this parallelism. With this short but thorough resource, data scientists and Python programmers will learn how the Dask open source library for parallel computing provides APIs that make it easy to parallelize PyData libraries including NumPy, pandas, and scikit-learn. Authors Holden Karau and Mika Kimmins show you how to use Dask computations in local systems and then scale to the cloud for heavier workloads. This practical book explains why Dask is popular among industry experts and academics and is used by organizations that include Walmart, Capital One, Harvard Medical School, and NASA. With this book, you'll learn: What Dask is, where you can use it, and how it compares with other tools How to use Dask for batch data parallel processing Key distributed system concepts for working with Dask Methods for using Dask with higher-level APIs and building blocks How to work with integrated libraries such as scikit-learn, pandas, and PyTorch How to use Dask with GPUs

Scaling Python with Dask

Author : Holden Karau
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1098119843
Total Pages : 226 pages
Book Rating : 4.0/5 (981 download)

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Book Synopsis Scaling Python with Dask by : Holden Karau

Download or read book Scaling Python with Dask written by Holden Karau and published by "O'Reilly Media, Inc.". This book was released on 2023-07-19 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern systems contain multi-core CPUs and GPUs that have the potential for parallel computing. But many scientific Python tools were not designed to leverage this parallelism. With this short but thorough resource, data scientists and Python programmers will learn how the Dask open source library for parallel computing provides APIs that make it easy to parallelize PyData libraries including NumPy, pandas, and scikit-learn. Authors Holden Karau and Mika Kimmins show you how to use Dask computations in local systems and then scale to the cloud for heavier workloads. This practical book explains why Dask is popular among industry experts and academics and is used by organizations that include Walmart, Capital One, Harvard Medical School, and NASA. With this book, you'll learn: What Dask is, where you can use it, and how it compares with other tools How to use Dask for batch data parallel processing Key distributed system concepts for working with Dask Methods for using Dask with higher-level APIs and building blocks How to work with integrated libraries such as scikit-learn, pandas, and PyTorch How to use Dask with GPUs

The Hacker's Guide to Scaling Python

Author : Julien Danjou
Publisher : Julien Danjou
ISBN 13 : 1387379321
Total Pages : 300 pages
Book Rating : 4.3/5 (873 download)

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Book Synopsis The Hacker's Guide to Scaling Python by : Julien Danjou

Download or read book The Hacker's Guide to Scaling Python written by Julien Danjou and published by Julien Danjou. This book was released on 2017 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: Python is a wonderful programming language that allows writing applications quickly. But how do you make those applications scale for thousands of users and requests? It takes years of practice, research, trial and errors to build experience and knowledge along the way. Simple questions such as "How do I make my code faster?" or "How do I make sure there is no bottleneck?" cost hours to find good answers. Without enough background on the topic, you'll never be sure that any answer you'll come up with will be correct. The Hacker's Guide to Scaling Python will help you solve that by providing guidelines, tips and best practice. Adding a few interviews of experts on the subject, you will learn how you can distribute your Python application so it is able to process thousands of requests.

Machine Learning Engineering with Python

Author : Andrew P. McMahon
Publisher : Packt Publishing Ltd
ISBN 13 : 1837634351
Total Pages : 463 pages
Book Rating : 4.8/5 (376 download)

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Book Synopsis Machine Learning Engineering with Python by : Andrew P. McMahon

Download or read book Machine Learning Engineering with Python written by Andrew P. McMahon and published by Packt Publishing Ltd. This book was released on 2023-08-31 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: Transform your machine learning projects into successful deployments with this practical guide on how to build and scale solutions that solve real-world problems Includes a new chapter on generative AI and large language models (LLMs) and building a pipeline that leverages LLMs using LangChain Key Features This second edition delves deeper into key machine learning topics, CI/CD, and system design Explore core MLOps practices, such as model management and performance monitoring Build end-to-end examples of deployable ML microservices and pipelines using AWS and open-source tools Book DescriptionThe Second Edition of Machine Learning Engineering with Python is the practical guide that MLOps and ML engineers need to build solutions to real-world problems. It will provide you with the skills you need to stay ahead in this rapidly evolving field. The book takes an examples-based approach to help you develop your skills and covers the technical concepts, implementation patterns, and development methodologies you need. You'll explore the key steps of the ML development lifecycle and create your own standardized "model factory" for training and retraining of models. You'll learn to employ concepts like CI/CD and how to detect different types of drift. Get hands-on with the latest in deployment architectures and discover methods for scaling up your solutions. This edition goes deeper in all aspects of ML engineering and MLOps, with emphasis on the latest open-source and cloud-based technologies. This includes a completely revamped approach to advanced pipelining and orchestration techniques. With a new chapter on deep learning, generative AI, and LLMOps, you will learn to use tools like LangChain, PyTorch, and Hugging Face to leverage LLMs for supercharged analysis. You will explore AI assistants like GitHub Copilot to become more productive, then dive deep into the engineering considerations of working with deep learning.What you will learn Plan and manage end-to-end ML development projects Explore deep learning, LLMs, and LLMOps to leverage generative AI Use Python to package your ML tools and scale up your solutions Get to grips with Apache Spark, Kubernetes, and Ray Build and run ML pipelines with Apache Airflow, ZenML, and Kubeflow Detect drift and build retraining mechanisms into your solutions Improve error handling with control flows and vulnerability scanning Host and build ML microservices and batch processes running on AWS Who this book is for This book is designed for MLOps and ML engineers, data scientists, and software developers who want to build robust solutions that use machine learning to solve real-world problems. If you’re not a developer but want to manage or understand the product lifecycle of these systems, you’ll also find this book useful. It assumes a basic knowledge of machine learning concepts and intermediate programming experience in Python. With its focus on practical skills and real-world examples, this book is an essential resource for anyone looking to advance their machine learning engineering career.

Geospatial Data Analytics on AWS

Author : Scott Bateman
Publisher : Packt Publishing Ltd
ISBN 13 : 1804610577
Total Pages : 276 pages
Book Rating : 4.8/5 (46 download)

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Book Synopsis Geospatial Data Analytics on AWS by : Scott Bateman

Download or read book Geospatial Data Analytics on AWS written by Scott Bateman and published by Packt Publishing Ltd. This book was released on 2023-06-30 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build an end-to-end geospatial data lake in AWS using popular AWS services such as RDS, Redshift, DynamoDB, and Athena to manage geodata Purchase of the print or Kindle book includes a free PDF eBook. Key Features Explore the architecture and different use cases to build and manage geospatial data lakes in AWS Discover how to leverage AWS purpose-built databases to store and analyze geospatial data Learn how to recognize which anti-patterns to avoid when managing geospatial data in the cloud Book DescriptionManaging geospatial data and building location-based applications in the cloud can be a daunting task. This comprehensive guide helps you overcome this challenge by presenting the concept of working with geospatial data in the cloud in an easy-to-understand way, along with teaching you how to design and build data lake architecture in AWS for geospatial data. You’ll begin by exploring the use of AWS databases like Redshift and Aurora PostgreSQL for storing and analyzing geospatial data. Next, you’ll leverage services such as DynamoDB and Athena, which offer powerful built-in geospatial functions for indexing and querying geospatial data. The book is filled with practical examples to illustrate the benefits of managing geospatial data in the cloud. As you advance, you’ll discover how to analyze and visualize data using Python and R, and utilize QuickSight to share derived insights. The concluding chapters explore the integration of commonly used platforms like Open Data on AWS, OpenStreetMap, and ArcGIS with AWS to enable you to optimize efficiency and provide a supportive community for continuous learning. By the end of this book, you’ll have the necessary tools and expertise to build and manage your own geospatial data lake on AWS, along with the knowledge needed to tackle geospatial data management challenges and make the most of AWS services.What you will learn Discover how to optimize the cloud to store your geospatial data Explore management strategies for your data repository using AWS Single Sign-On and IAM Create effective SQL queries against your geospatial data using Athena Validate postal addresses using Amazon Location services Process structured and unstructured geospatial data efficiently using R Use Amazon SageMaker to enable machine learning features in your application Explore the free and subscription satellite imagery data available for use in your GIS Who this book is forIf you understand the importance of accurate coordinates, but not necessarily the cloud, then this book is for you. This book is best suited for GIS developers, GIS analysts, data analysts, and data scientists looking to enhance their solutions with geospatial data for cloud-centric applications. A basic understanding of geographic concepts is suggested, but no experience with the cloud is necessary for understanding the concepts in this book.

Python Playground, 2nd Edition

Author : Mahesh Venkitachalam
Publisher : No Starch Press
ISBN 13 : 1718503059
Total Pages : 447 pages
Book Rating : 4.7/5 (185 download)

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Book Synopsis Python Playground, 2nd Edition by : Mahesh Venkitachalam

Download or read book Python Playground, 2nd Edition written by Mahesh Venkitachalam and published by No Starch Press. This book was released on 2023-11-28 with total page 447 pages. Available in PDF, EPUB and Kindle. Book excerpt: Put the fun back in Python programming and build your skills as you create 3D simulations and graphics, speech-recognition machine-learning systems, IoT devices, and more. The fully updated 2nd edition is here, now with 5 brand-new projects! Harness the power of Python as you turn code into tangible creations with Python Playground, a collection of 15 inventive projects that will expand your programming horizons, spark your curiosity, and elevate your coding skills. Go beyond the basics as you write programs to generate art and music, simulate real-world phenomena, and interact with hardware, all through the use of Python and common libraries such as numpy, matplotlib, and Pillow. As you work through the book’s projects, you will: Craft intricate Spirograph-like designs with parametric equations and the turtle module Generate music by synthesizing plucked string sounds Transform everyday images into ASCII art, photomosaics, and eye-popping autostereograms Design engaging cellular automata and flocking simulations Explore the realm of 3D graphics, from basic shape rendering to visualizing MRI scan data Build a Raspberry Pi–powered laser show that dances along with music New to this edition: We’ve expanded your playground with five new projects: you’ll draw fractals, bring Conway’s Game of Life into 3D space, and use a Raspberry Pi and Python to create a musical instrument, an IoT garden monitor, and even a machine learning–driven speech recognition system. Whether you’re a seasoned professional or just getting started, you’ll find Python Playground to be a great way to learn, experiment with, and master this versatile programming language. Covers Python 3.x

Automated Technology for Verification and Analysis

Author : Étienne André
Publisher : Springer Nature
ISBN 13 : 3031453298
Total Pages : 453 pages
Book Rating : 4.0/5 (314 download)

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Book Synopsis Automated Technology for Verification and Analysis by : Étienne André

Download or read book Automated Technology for Verification and Analysis written by Étienne André and published by Springer Nature. This book was released on 2023-10-21 with total page 453 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 21st International Symposium on Automated Technology for Verification and Analysis, ATVA 2023, held in Singapore, in October 2023. The symposium intends to promote research in theoretical and practical aspects of automated analysis, verification and synthesis by providing a forum for interaction between regional and international research communities and industry in related areas. The 30 regular papers presented together with 7 tool papers were carefully reviewed and selected from 150 submissions.The papers are divided into the following topical sub-headings: Temporal logics, Data structures and heuristics, Verification of programs and hardware.

High Performance Computing

Author : Amanda Bienz
Publisher : Springer Nature
ISBN 13 : 3031408438
Total Pages : 677 pages
Book Rating : 4.0/5 (314 download)

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Book Synopsis High Performance Computing by : Amanda Bienz

Download or read book High Performance Computing written by Amanda Bienz and published by Springer Nature. This book was released on 2023-09-25 with total page 677 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume constitutes the papers of several workshops which were held in conjunction with the 38th International Conference on High Performance Computing, ISC High Performance 2023, held in Hamburg, Germany, during May 21–25, 2023. The 49 revised full papers presented in this book were carefully reviewed and selected from 70 submissions. ISC High Performance 2023 presents the following workshops: 2nd International Workshop on Malleability Techniques Applications in High-Performance Computing (HPCMALL) 18th Workshop on Virtualization in High-Performance Cloud Computing (VHPC 23) HPC I/O in the Data Center (HPC IODC) Workshop on Converged Computing of Cloud, HPC, and Edge (WOCC’23) 7th International Workshop on In Situ Visualization (WOIV’23) Workshop on Monitoring and Operational Data Analytics (MODA23) 2nd Workshop on Communication, I/O, and Storage at Scale on Next-Generation Platforms: Scalable Infrastructures First International Workshop on RISC-V for HPC Second Combined Workshop on Interactive and Urgent Supercomputing (CWIUS) HPC on Heterogeneous Hardware (H3)

Python Playground

Author : Mahesh Venkitachalam
Publisher : No Starch Press
ISBN 13 : 1593277334
Total Pages : 353 pages
Book Rating : 4.5/5 (932 download)

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Book Synopsis Python Playground by : Mahesh Venkitachalam

Download or read book Python Playground written by Mahesh Venkitachalam and published by No Starch Press. This book was released on 2015-10-01 with total page 353 pages. Available in PDF, EPUB and Kindle. Book excerpt: Python is a powerful programming language that’s easy to learn and fun to play with. But once you’ve gotten a handle on the basics, what do you do next? Python Playground is a collection of imaginative programming projects that will inspire you to use Python to make art and music, build simulations of real-world phenomena, and interact with hardware like the Arduino and Raspberry Pi. You’ll learn to use common Python tools and libraries like numpy, matplotlib, and pygame to do things like: –Generate Spirograph-like patterns using parametric equations and the turtle module –Create music on your computer by simulating frequency overtones –Translate graphical images into ASCII art –Write an autostereogram program that produces 3D images hidden beneath random patterns –Make realistic animations with OpenGL shaders by exploring particle systems, transparency, and billboarding techniques –Construct 3D visualizations using data from CT and MRI scans –Build a laser show that responds to music by hooking up your computer to an Arduino Programming shouldn’t be a chore. Have some solid, geeky fun with Python Playground. The projects in this book are compatible with both Python 2 and 3.

Generative AI with LangChain

Author : Ben Auffarth
Publisher : Packt Publishing Ltd
ISBN 13 : 1835088368
Total Pages : 369 pages
Book Rating : 4.8/5 (35 download)

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Book Synopsis Generative AI with LangChain by : Ben Auffarth

Download or read book Generative AI with LangChain written by Ben Auffarth and published by Packt Publishing Ltd. This book was released on 2023-12-22 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt: 2024 Edition – Get to grips with the LangChain framework to develop production-ready applications, including agents and personal assistants. The 2024 edition features updated code examples and an improved GitHub repository. Purchase of the print or Kindle book includes a free PDF eBook. Key Features Learn how to leverage LangChain to work around LLMs’ inherent weaknesses Delve into LLMs with LangChain and explore their fundamentals, ethical dimensions, and application challenges Get better at using ChatGPT and GPT models, from heuristics and training to scalable deployment, empowering you to transform ideas into reality Book DescriptionChatGPT and the GPT models by OpenAI have brought about a revolution not only in how we write and research but also in how we can process information. This book discusses the functioning, capabilities, and limitations of LLMs underlying chat systems, including ChatGPT and Gemini. It demonstrates, in a series of practical examples, how to use the LangChain framework to build production-ready and responsive LLM applications for tasks ranging from customer support to software development assistance and data analysis – illustrating the expansive utility of LLMs in real-world applications. Unlock the full potential of LLMs within your projects as you navigate through guidance on fine-tuning, prompt engineering, and best practices for deployment and monitoring in production environments. Whether you're building creative writing tools, developing sophisticated chatbots, or crafting cutting-edge software development aids, this book will be your roadmap to mastering the transformative power of generative AI with confidence and creativity.What you will learn Create LLM apps with LangChain, like question-answering systems and chatbots Understand transformer models and attention mechanisms Automate data analysis and visualization using pandas and Python Grasp prompt engineering to improve performance Fine-tune LLMs and get to know the tools to unleash their power Deploy LLMs as a service with LangChain and apply evaluation strategies Privately interact with documents using open-source LLMs to prevent data leaks Who this book is for The book is for developers, researchers, and anyone interested in learning more about LangChain. Whether you are a beginner or an experienced developer, this book will serve as a valuable resource if you want to get the most out of LLMs using LangChain. Basic knowledge of Python is a prerequisite, while prior exposure to machine learning will help you follow along more easily.

Deep Learning Illustrated

Author : Jon Krohn
Publisher : Addison-Wesley Professional
ISBN 13 : 0135121728
Total Pages : 725 pages
Book Rating : 4.1/5 (351 download)

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Book Synopsis Deep Learning Illustrated by : Jon Krohn

Download or read book Deep Learning Illustrated written by Jon Krohn and published by Addison-Wesley Professional. This book was released on 2019-08-05 with total page 725 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The authors’ clear visual style provides a comprehensive look at what’s currently possible with artificial neural networks as well as a glimpse of the magic that’s to come." – Tim Urban, author of Wait But Why Fully Practical, Insightful Guide to Modern Deep Learning Deep learning is transforming software, facilitating powerful new artificial intelligence capabilities, and driving unprecedented algorithm performance. Deep Learning Illustrated is uniquely intuitive and offers a complete introduction to the discipline’s techniques. Packed with full-color figures and easy-to-follow code, it sweeps away the complexity of building deep learning models, making the subject approachable and fun to learn. World-class instructor and practitioner Jon Krohn–with visionary content from Grant Beyleveld and beautiful illustrations by Aglaé Bassens–presents straightforward analogies to explain what deep learning is, why it has become so popular, and how it relates to other machine learning approaches. Krohn has created a practical reference and tutorial for developers, data scientists, researchers, analysts, and students who want to start applying it. He illuminates theory with hands-on Python code in accompanying Jupyter notebooks. To help you progress quickly, he focuses on the versatile deep learning library Keras to nimbly construct efficient TensorFlow models; PyTorch, the leading alternative library, is also covered. You’ll gain a pragmatic understanding of all major deep learning approaches and their uses in applications ranging from machine vision and natural language processing to image generation and game-playing algorithms. Discover what makes deep learning systems unique, and the implications for practitioners Explore new tools that make deep learning models easier to build, use, and improve Master essential theory: artificial neurons, training, optimization, convolutional nets, recurrent nets, generative adversarial networks (GANs), deep reinforcement learning, and more Walk through building interactive deep learning applications, and move forward with your own artificial intelligence projects Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.

Euro-Par 2024: Parallel Processing

Author : Jesus Carretero
Publisher : Springer Nature
ISBN 13 : 3031695771
Total Pages : 430 pages
Book Rating : 4.0/5 (316 download)

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Book Synopsis Euro-Par 2024: Parallel Processing by : Jesus Carretero

Download or read book Euro-Par 2024: Parallel Processing written by Jesus Carretero and published by Springer Nature. This book was released on with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Snakes on a spaceship—An overview of python in space physics

Author : Angeline G. Burrell
Publisher : Frontiers Media SA
ISBN 13 : 2832529593
Total Pages : 436 pages
Book Rating : 4.8/5 (325 download)

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Book Synopsis Snakes on a spaceship—An overview of python in space physics by : Angeline G. Burrell

Download or read book Snakes on a spaceship—An overview of python in space physics written by Angeline G. Burrell and published by Frontiers Media SA. This book was released on 2023-07-20 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Production-Ready Applied Deep Learning

Author : Tomasz Palczewski
Publisher : Packt Publishing Ltd
ISBN 13 : 1803238054
Total Pages : 322 pages
Book Rating : 4.8/5 (32 download)

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Book Synopsis Production-Ready Applied Deep Learning by : Tomasz Palczewski

Download or read book Production-Ready Applied Deep Learning written by Tomasz Palczewski and published by Packt Publishing Ltd. This book was released on 2022-08-30 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: Supercharge your skills for developing powerful deep learning models and distributing them at scale efficiently using cloud services Key Features Understand how to execute a deep learning project effectively using various tools available Learn how to develop PyTorch and TensorFlow models at scale using Amazon Web Services Explore effective solutions to various difficulties that arise from model deployment Book Description Machine learning engineers, deep learning specialists, and data engineers encounter various problems when moving deep learning models to a production environment. The main objective of this book is to close the gap between theory and applications by providing a thorough explanation of how to transform various models for deployment and efficiently distribute them with a full understanding of the alternatives. First, you will learn how to construct complex deep learning models in PyTorch and TensorFlow. Next, you will acquire the knowledge you need to transform your models from one framework to the other and learn how to tailor them for specific requirements that deployment environments introduce. The book also provides concrete implementations and associated methodologies that will help you apply the knowledge you gain right away. You will get hands-on experience with commonly used deep learning frameworks and popular cloud services designed for data analytics at scale. Additionally, you will get to grips with the authors' collective knowledge of deploying hundreds of AI-based services at a large scale. By the end of this book, you will have understood how to convert a model developed for proof of concept into a production-ready application optimized for a particular production setting. What you will learn Understand how to develop a deep learning model using PyTorch and TensorFlow Convert a proof-of-concept model into a production-ready application Discover how to set up a deep learning pipeline in an efficient way using AWS Explore different ways to compress a model for various deployment requirements Develop Android and iOS applications that run deep learning on mobile devices Monitor a system with a deep learning model in production Choose the right system architecture for developing and deploying a model Who this book is for Machine learning engineers, deep learning specialists, and data scientists will find this book helpful in closing the gap between the theory and application with detailed examples. Beginner-level knowledge in machine learning or software engineering will help you grasp the concepts covered in this book easily.

Learning Path

Author : Katharine Jarmul
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (113 download)

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Book Synopsis Learning Path by : Katharine Jarmul

Download or read book Learning Path written by Katharine Jarmul and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "If you have some Python experience, and you want to take it to the next level, this practical, hands-on Learning Path will be a helpful resource. Video tutorials in this Learning Path will show you how to use Python for distributed task processing, perform large-scale data processing in Spark using the PySpark API, and tackle machine learning tasks with Python."--Resource description page.