Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
A General Machine Reading Comprehension Pipeline
Download A General Machine Reading Comprehension Pipeline full books in PDF, epub, and Kindle. Read online A General Machine Reading Comprehension Pipeline ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis Building Machine Learning Pipelines by : Hannes Hapke
Download or read book Building Machine Learning Pipelines written by Hannes Hapke and published by "O'Reilly Media, Inc.". This book was released on 2020-07-13 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: Companies are spending billions on machine learning projects, but it’s money wasted if the models can’t be deployed effectively. In this practical guide, Hannes Hapke and Catherine Nelson walk you through the steps of automating a machine learning pipeline using the TensorFlow ecosystem. You’ll learn the techniques and tools that will cut deployment time from days to minutes, so that you can focus on developing new models rather than maintaining legacy systems. Data scientists, machine learning engineers, and DevOps engineers will discover how to go beyond model development to successfully productize their data science projects, while managers will better understand the role they play in helping to accelerate these projects. Understand the steps to build a machine learning pipeline Build your pipeline using components from TensorFlow Extended Orchestrate your machine learning pipeline with Apache Beam, Apache Airflow, and Kubeflow Pipelines Work with data using TensorFlow Data Validation and TensorFlow Transform Analyze a model in detail using TensorFlow Model Analysis Examine fairness and bias in your model performance Deploy models with TensorFlow Serving or TensorFlow Lite for mobile devices Learn privacy-preserving machine learning techniques
Book Synopsis Data Science in Production by : Ben Weber
Download or read book Data Science in Production written by Ben Weber and published by . This book was released on 2020 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt: Putting predictive models into production is one of the most direct ways that data scientists can add value to an organization. By learning how to build and deploy scalable model pipelines, data scientists can own more of the model production process and more rapidly deliver data products. This book provides a hands-on approach to scaling up Python code to work in distributed environments in order to build robust pipelines. Readers will learn how to set up machine learning models as web endpoints, serverless functions, and streaming pipelines using multiple cloud environments. It is intended for analytics practitioners with hands-on experience with Python libraries such as Pandas and scikit-learn, and will focus on scaling up prototype models to production. From startups to trillion dollar companies, data science is playing an important role in helping organizations maximize the value of their data. This book helps data scientists to level up their careers by taking ownership of data products with applied examples that demonstrate how to: Translate models developed on a laptop to scalable deployments in the cloud Develop end-to-end systems that automate data science workflows Own a data product from conception to production The accompanying Jupyter notebooks provide examples of scalable pipelines across multiple cloud environments, tools, and libraries (github.com/bgweber/DS_Production). Book Contents Here are the topics covered by Data Science in Production: Chapter 1: Introduction - This chapter will motivate the use of Python and discuss the discipline of applied data science, present the data sets, models, and cloud environments used throughout the book, and provide an overview of automated feature engineering. Chapter 2: Models as Web Endpoints - This chapter shows how to use web endpoints for consuming data and hosting machine learning models as endpoints using the Flask and Gunicorn libraries. We'll start with scikit-learn models and also set up a deep learning endpoint with Keras. Chapter 3: Models as Serverless Functions - This chapter will build upon the previous chapter and show how to set up model endpoints as serverless functions using AWS Lambda and GCP Cloud Functions. Chapter 4: Containers for Reproducible Models - This chapter will show how to use containers for deploying models with Docker. We'll also explore scaling up with ECS and Kubernetes, and building web applications with Plotly Dash. Chapter 5: Workflow Tools for Model Pipelines - This chapter focuses on scheduling automated workflows using Apache Airflow. We'll set up a model that pulls data from BigQuery, applies a model, and saves the results. Chapter 6: PySpark for Batch Modeling - This chapter will introduce readers to PySpark using the community edition of Databricks. We'll build a batch model pipeline that pulls data from a data lake, generates features, applies a model, and stores the results to a No SQL database. Chapter 7: Cloud Dataflow for Batch Modeling - This chapter will introduce the core components of Cloud Dataflow and implement a batch model pipeline for reading data from BigQuery, applying an ML model, and saving the results to Cloud Datastore. Chapter 8: Streaming Model Workflows - This chapter will introduce readers to Kafka and PubSub for streaming messages in a cloud environment. After working through this material, readers will learn how to use these message brokers to create streaming model pipelines with PySpark and Dataflow that provide near real-time predictions. Excerpts of these chapters are available on Medium (@bgweber), and a book sample is available on Leanpub.
Book Synopsis Applied Text Analysis with Python by : Benjamin Bengfort
Download or read book Applied Text Analysis with Python written by Benjamin Bengfort and published by "O'Reilly Media, Inc.". This book was released on 2018-06-11 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: From news and speeches to informal chatter on social media, natural language is one of the richest and most underutilized sources of data. Not only does it come in a constant stream, always changing and adapting in context; it also contains information that is not conveyed by traditional data sources. The key to unlocking natural language is through the creative application of text analytics. This practical book presents a data scientist’s approach to building language-aware products with applied machine learning. You’ll learn robust, repeatable, and scalable techniques for text analysis with Python, including contextual and linguistic feature engineering, vectorization, classification, topic modeling, entity resolution, graph analysis, and visual steering. By the end of the book, you’ll be equipped with practical methods to solve any number of complex real-world problems. Preprocess and vectorize text into high-dimensional feature representations Perform document classification and topic modeling Steer the model selection process with visual diagnostics Extract key phrases, named entities, and graph structures to reason about data in text Build a dialog framework to enable chatbots and language-driven interaction Use Spark to scale processing power and neural networks to scale model complexity
Book Synopsis Operationalizing Machine Learning Pipelines by : Vishwajyoti Pandey
Download or read book Operationalizing Machine Learning Pipelines written by Vishwajyoti Pandey and published by BPB Publications. This book was released on 2022-02-22 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: Implementing ML pipelines using MLOps KEY FEATURES ● In-depth knowledge of MLOps, including recommendations for tools and processes. ● Includes only open-source cloud-agnostic tools for demonstrating MLOps. ● Covers end-to-end examples of implementing the whole process on Google Cloud Platform. DESCRIPTION This book will provide you with an in-depth understanding of MLOps and how you can use it inside an enterprise. Each tool discussed in this book has been thoroughly examined, providing examples of how to install and use them, as well as sample data. This book will teach you about every stage of the machine learning lifecycle and how to implement them within an organisation using a machine learning framework. With GitOps, you'll learn how to automate operations and create reusable components such as feature stores for use in various contexts. You will learn to create a server-less training and deployment platform that scales automatically based on demand. You will learn about Polyaxon for machine learning model training, and KFServing, for model deployment. Additionally, you will understand how you should monitor machine learning models in production and what factors can degrade the model's performance. You can apply the knowledge gained from this book to adopt MLOps in your organisation and tailor the requirements to your specific project. As you keep an eye on the model's performance, you'll be able to train and deploy it more quickly and with greater confidence. WHAT YOU WILL LEARN ● Quick grasp of the entire machine learning lifecycle and tricks to manage all components. ● Learn to train and validate machine learning models for scalability. ● Get to know the pros of cloud computing for scaling ML operations. ● Covers aspects of ML operations, such as reproducibility and scalability, in detail. ● Get to know how to monitor machine learning models in production. ● Learn and practice automating the ML training and deployment processes. WHO THIS BOOK IS FOR This book is intended for machine learning specialists, data scientists, and data engineers who wish to improve and increase their MLOps knowledge to streamline machine learning initiatives. Readers with a working knowledge of the machine learning lifecycle would be advantageous. TABLE OF CONTENTS 1. DS/ML Projects – Initial Setup 2. ML Projects Lifecycle 3. ML Architecture – Framework and Components 4. Data Exploration and Quantifying Business Problem 5. Training & Testing ML model 6. ML model performance measurement 7. CRUD operations with different JavaScript frameworks 8. Feature Store 9. Building ML Pipeline
Book Synopsis Intelligent Information and Database Systems by : Ngoc Thanh Nguyen
Download or read book Intelligent Information and Database Systems written by Ngoc Thanh Nguyen and published by Springer Nature. This book was released on 2023-09-04 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set LNAI 13995 and LNAI 13996 constitutes the refereed proceedings of the 15th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2023, held in Phuket, Thailand, during July 24–26, 2023. The 65 full papers presented in these proceedings were carefully reviewed and selected from 224 submissions. The papers of the 2 volume-set are organized in the following topical sections: Case-Based Reasoning and Machine Comprehension; Computer Vision; Data Mining and Machine Learning; Knowledge Integration and Analysis; Speech and Text Processing; and Resource Management and Optimization.
Book Synopsis New Frontiers in Artificial Intelligence by : Katsutoshi Yada
Download or read book New Frontiers in Artificial Intelligence written by Katsutoshi Yada and published by Springer Nature. This book was released on 2023-07-18 with total page 403 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes extended, revised, and selected papers from the 13th International Symposium on Artificial Intelligence supported by the Japanese Society for Artificial Intelligence, JSAI-isAI 2021, held online in November 2021. The 26 full papers were carefully selected from 86 submissions. The papers are organized in the volume according to the following workshops: 15th International Workshop on Juris-Informatics, JURISIN 2021; 18th Workshop on Logic and Engineering of Natural Language Semantics, LENLS 18, 5th International Workshop on SCIentific DOCument Analysis, SCI-DOCA 2021; Workshop on Artificial Affective (Kansei) Intelligence, KANSEI-AI 2021; 5th Workshop on Artificial Intelligence of and for Business, AI-Biz 2021.
Download or read book ECAI 2023 written by K. Gal and published by IOS Press. This book was released on 2023-10-18 with total page 3328 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence, or AI, now affects the day-to-day life of almost everyone on the planet, and continues to be a perennial hot topic in the news. This book presents the proceedings of ECAI 2023, the 26th European Conference on Artificial Intelligence, and of PAIS 2023, the 12th Conference on Prestigious Applications of Intelligent Systems, held from 30 September to 4 October 2023 and on 3 October 2023 respectively in Kraków, Poland. Since 1974, ECAI has been the premier venue for presenting AI research in Europe, and this annual conference has become the place for researchers and practitioners of AI to discuss the latest trends and challenges in all subfields of AI, and to demonstrate innovative applications and uses of advanced AI technology. ECAI 2023 received 1896 submissions – a record number – of which 1691 were retained for review, ultimately resulting in an acceptance rate of 23%. The 390 papers included here, cover topics including machine learning, natural language processing, multi agent systems, and vision and knowledge representation and reasoning. PAIS 2023 received 17 submissions, of which 10 were accepted after a rigorous review process. Those 10 papers cover topics ranging from fostering better working environments, behavior modeling and citizen science to large language models and neuro-symbolic applications, and are also included here. Presenting a comprehensive overview of current research and developments in AI, the book will be of interest to all those working in the field.
Book Synopsis The Architecture of High Performance Computers by : IBBETT
Download or read book The Architecture of High Performance Computers written by IBBETT and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction 1. 1 Historical Developments 1 1. 2 Techniques for Improving Performance 2 1. 3 An Architectural Design Example 3 2 Instructions and Addresses 2. 1 Three-address Systems - The CDC 6600 and 7600 7 2. 2 Two-address Systems - The IBM System/360 and /370 10 2. 3 One-address Systems 12 2. 4 Zero-address Systems 15 2. 5 The MU5 Instruction Set 17 2. 6 Comparing Instruction Formats 22 3 Storage Hierarcbies 3. 1 Store Interleaving 26 3. 2 The Atlas Paging System 29 3. 3 IBM Cache Systems 33 3. 4 The MU5 Name Store 37 3. 5 Data Transfers in the MU5 Storage Hierarchy 44 4 Pipelines 4. 1 The MU5 Primary Operand Unit Pipeline 49 4. 2 Arithmetic Pipelines - The TI ASC 62 4. 3 The IBM System/360 Model 91 Common Data Bus 67 5 Instruction Buffering 5. 1 The IBM System/360 Model 195 Instruction Processor 72 5. 2 Instruction Buffering in CDC Computers 77 5. 3 The MU5 Instruction Buffer Unit 82 5. 4 The CRAY-1 Instruction Buffers 87 5. 5 Position of the Control Point 89 6 Parallel Functional Units 6. 1 The CDC 6600 Central Processor 95 6. 2 The CDC 7600 Central Processor 104 6. 3 Performance 110 6 • 4 The CRA Y-1 112 7 Vector Processors 7. 1 Vector Facilities in MU5 126 7. 2 String Operations in MU5 136 7. 3 The CDC Star-100 142 7. 4 The CDC CYBER 205 146 7.
Book Synopsis Machine Learning for Cyber Security by : Yuan Xu
Download or read book Machine Learning for Cyber Security written by Yuan Xu and published by Springer Nature. This book was released on 2023-01-12 with total page 694 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-volume proceedings set LNCS 13655,13656 and 13657 constitutes the refereedproceedings of the 4th International Conference on Machine Learning for Cyber Security, ML4CS 2022, which taking place during December 2–4, 2022, held in Guangzhou, China. The 100 full papers and 46 short papers were included in these proceedings were carefully reviewed and selected from 367 submissions.
Book Synopsis Grokking Machine Learning by : Luis Serrano
Download or read book Grokking Machine Learning written by Luis Serrano and published by Simon and Schuster. This book was released on 2021-12-14 with total page 510 pages. Available in PDF, EPUB and Kindle. Book excerpt: Grokking Machine Learning presents machine learning algorithms and techniques in a way that anyone can understand. This book skips the confused academic jargon and offers clear explanations that require only basic algebra. As you go, you'll build interesting projects with Python, including models for spam detection and image recognition. You'll also pick up practical skills for cleaning and preparing data.
Book Synopsis Introduction to Machine Learning with Python by : Andreas C. Müller
Download or read book Introduction to Machine Learning with Python written by Andreas C. Müller and published by "O'Reilly Media, Inc.". This book was released on 2016-09-26 with total page 429 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination. You’ll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Müller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book. With this book, you’ll learn: Fundamental concepts and applications of machine learning Advantages and shortcomings of widely used machine learning algorithms How to represent data processed by machine learning, including which data aspects to focus on Advanced methods for model evaluation and parameter tuning The concept of pipelines for chaining models and encapsulating your workflow Methods for working with text data, including text-specific processing techniques Suggestions for improving your machine learning and data science skills
Book Synopsis Oil and Gas Pipelines in Nontechnical Language, 2nd Edition by : Thomas O. Miesner
Download or read book Oil and Gas Pipelines in Nontechnical Language, 2nd Edition written by Thomas O. Miesner and published by Pennwell Books. This book was released on 2020-07 with total page 395 pages. Available in PDF, EPUB and Kindle. Book excerpt: A totally understandable view of pipeline inception, planning, construction, start-up, and operation.
Download or read book The Engineer written by and published by . This book was released on 1867 with total page 677 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Mathematics for Machine Learning by : Marc Peter Deisenroth
Download or read book Mathematics for Machine Learning written by Marc Peter Deisenroth and published by Cambridge University Press. This book was released on 2020-04-23 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.
Book Synopsis CUET PG General Paper [COQP11] 20 Mock Test With Detail Solution As Per Updated Syllabus [25 MCQ in Each Mock Test] by : DIWAKAR EDUCATION HUB
Download or read book CUET PG General Paper [COQP11] 20 Mock Test With Detail Solution As Per Updated Syllabus [25 MCQ in Each Mock Test] written by DIWAKAR EDUCATION HUB and published by DIWAKAR EDUCATION HUB. This book was released on 2023-10-30 with total page 95 pages. Available in PDF, EPUB and Kindle. Book excerpt: CUET-PG 20 Mock Test With Solution Most Expected MCQ As Per Updated Syllabus 2024 Highlight of Question Bank- -In Each Mock Test Given 25 MCQ With Solution of Each Questions - All Questions Selected As Per Past Year Paper Asked Questions - Design by Qualified Faculty - Best Practice Mock Test
Book Synopsis United States Code by : United States
Download or read book United States Code written by United States and published by . This book was released on 2013 with total page 1358 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The United States Code is the official codification of the general and permanent laws of the United States of America. The Code was first published in 1926, and a new edition of the code has been published every six years since 1934. The 2012 edition of the Code incorporates laws enacted through the One Hundred Twelfth Congress, Second Session, the last of which was signed by the President on January 15, 2013. It does not include laws of the One Hundred Thirteenth Congress, First Session, enacted between January 2, 2013, the date it convened, and January 15, 2013. By statutory authority this edition may be cited "U.S.C. 2012 ed." As adopted in 1926, the Code established prima facie the general and permanent laws of the United States. The underlying statutes reprinted in the Code remained in effect and controlled over the Code in case of any discrepancy. In 1947, Congress began enacting individual titles of the Code into positive law. When a title is enacted into positive law, the underlying statutes are repealed and the title then becomes legal evidence of the law. Currently, 26 of the 51 titles in the Code have been so enacted. These are identified in the table of titles near the beginning of each volume. The Law Revision Counsel of the House of Representatives continues to prepare legislation pursuant to 2 U.S.C. 285b to enact the remainder of the Code, on a title-by-title basis, into positive law. The 2012 edition of the Code was prepared and published under the supervision of Ralph V. Seep, Law Revision Counsel. Grateful acknowledgment is made of the contributions by all who helped in this work, particularly the staffs of the Office of the Law Revision Counsel and the Government Printing Office"--Preface.
Book Synopsis Proceedings of the 2022 3rd International Conference on Artificial Intelligence and Education (IC-ICAIE 2022) by : Bob Fox
Download or read book Proceedings of the 2022 3rd International Conference on Artificial Intelligence and Education (IC-ICAIE 2022) written by Bob Fox and published by Springer Nature. This book was released on 2023-01-20 with total page 1656 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is an open access book. The 2022 3rd International Conference on Artificial Intelligence and Education(ICAIE 2022) will be held in Chengdu, China during June 24-26, 2022. The meeting focused on the new trends in the development of "artificial intelligence" and "education" under the new situation, and jointly discussed how to empower and promote the high-quality development of "artificial intelligence" and "education". An ideal platform to share views and experiences with industry experts. The conference invites experts and scholars in the field to conduct wonderful exchanges based on their own research results based on the development of the times. The themes are around artificial intelligence technology and applications; intelligent and knowledge-based systems; information-based education; intelligent learning; advanced information theory and neural network technology ; software computing and algorithms; intelligent algorithms and computing and many other topics.
![Download CUET PG General Paper [COQP11] 20 Mock Test With Detail Solution As Per Updated Syllabus [25 MCQ in Each Mock Test] PDF Online Free](https://books.google.com/books/content/images/frontcover/qu3fEAAAQBAJ?fife=w200-h370)
