Practical Weak Supervision

Practical Weak Supervision Book in PDF, ePub and Kindle version is available to download in english. Read online anytime anywhere directly from your device. Click on the download button below to get a free pdf file of Practical Weak Supervision book. This book definitely worth reading, it is an incredibly well-written.

Practical Weak Supervision

Author : Wee-Hyong Tok,Amit Bahree,Senja Filipi
Publisher : O'Reilly Media
Page : 0 pages
File Size : 54,7 Mb
Release : 2021-10-15
Category : Computer vision
ISBN : 1492077062

Get Book

Practical Weak Supervision by Wee-Hyong Tok,Amit Bahree,Senja Filipi Pdf

Most data scientists and engineers today rely on quality labeled data to train their machine learning models. But building training sets manually is time-consuming and expensive, leaving many companies with unfinished ML projects. There's a more practical approach. In this book, Amit Bahree, Senja Filipi, and Wee Hyong Tok from Microsoft show you how to create products using weakly supervised learning models. You'll learn how to build natural language processing and computer vision projects using weakly labeled datasets from Snorkel, a spin-off from the Stanford AI Lab. Because so many companies pursue ML projects that never go beyond their labs, this book also provides a guide on how to ship the deep learning models you build. Get a practical overview of weak supervision Dive into data programming with help from Snorkel Perform text classification using Snorkel's weakly labeled dataset Use Snorkel's labeled indoor-outdoor dataset for computer vision tasks Scale up weak supervision using scaling strategies and underlying technologies.

Practical Weak Supervision

Author : Wee Hyong Tok,Amit Bahree,Senja Filipi
Publisher : "O'Reilly Media, Inc."
Page : 192 pages
File Size : 54,8 Mb
Release : 2021-09-30
Category : Computers
ISBN : 9781492077015

Get Book

Practical Weak Supervision by Wee Hyong Tok,Amit Bahree,Senja Filipi Pdf

Most data scientists and engineers today rely on quality labeled data to train machine learning models. But building a training set manually is time-consuming and expensive, leaving many companies with unfinished ML projects. There's a more practical approach. In this book, Wee Hyong Tok, Amit Bahree, and Senja Filipi show you how to create products using weakly supervised learning models. You'll learn how to build natural language processing and computer vision projects using weakly labeled datasets from Snorkel, a spin-off from the Stanford AI Lab. Because so many companies have pursued ML projects that never go beyond their labs, this book also provides a guide on how to ship the deep learning models you build. Get up to speed on the field of weak supervision, including ways to use it as part of the data science process Use Snorkel AI for weak supervision and data programming Get code examples for using Snorkel to label text and image datasets Use a weakly labeled dataset for text and image classification Learn practical considerations for using Snorkel with large datasets and using Spark clusters to scale labeling

Machine Learning for Data Streams

Author : Albert Bifet,Ricard Gavalda,Geoffrey Holmes,Bernhard Pfahringer
Publisher : MIT Press
Page : 289 pages
File Size : 42,6 Mb
Release : 2023-05-09
Category : Computers
ISBN : 9780262547833

Get Book

Machine Learning for Data Streams by Albert Bifet,Ricard Gavalda,Geoffrey Holmes,Bernhard Pfahringer Pdf

A hands-on approach to tasks and techniques in data stream mining and real-time analytics, with examples in MOA, a popular freely available open-source software framework. Today many information sources—including sensor networks, financial markets, social networks, and healthcare monitoring—are so-called data streams, arriving sequentially and at high speed. Analysis must take place in real time, with partial data and without the capacity to store the entire data set. This book presents algorithms and techniques used in data stream mining and real-time analytics. Taking a hands-on approach, the book demonstrates the techniques using MOA (Massive Online Analysis), a popular, freely available open-source software framework, allowing readers to try out the techniques after reading the explanations. The book first offers a brief introduction to the topic, covering big data mining, basic methodologies for mining data streams, and a simple example of MOA. More detailed discussions follow, with chapters on sketching techniques, change, classification, ensemble methods, regression, clustering, and frequent pattern mining. Most of these chapters include exercises, an MOA-based lab session, or both. Finally, the book discusses the MOA software, covering the MOA graphical user interface, the command line, use of its API, and the development of new methods within MOA. The book will be an essential reference for readers who want to use data stream mining as a tool, researchers in innovation or data stream mining, and programmers who want to create new algorithms for MOA.

Machine Learning and Data Science Blueprints for Finance

Author : Hariom Tatsat,Sahil Puri,Brad Lookabaugh
Publisher : "O'Reilly Media, Inc."
Page : 432 pages
File Size : 47,8 Mb
Release : 2020-10-01
Category : Computers
ISBN : 9781492073000

Get Book

Machine Learning and Data Science Blueprints for Finance by Hariom Tatsat,Sahil Puri,Brad Lookabaugh Pdf

Over the next few decades, machine learning and data science will transform the finance industry. With this practical book, analysts, traders, researchers, and developers will learn how to build machine learning algorithms crucial to the industry. You’ll examine ML concepts and over 20 case studies in supervised, unsupervised, and reinforcement learning, along with natural language processing (NLP). Ideal for professionals working at hedge funds, investment and retail banks, and fintech firms, this book also delves deep into portfolio management, algorithmic trading, derivative pricing, fraud detection, asset price prediction, sentiment analysis, and chatbot development. You’ll explore real-life problems faced by practitioners and learn scientifically sound solutions supported by code and examples. This book covers: Supervised learning regression-based models for trading strategies, derivative pricing, and portfolio management Supervised learning classification-based models for credit default risk prediction, fraud detection, and trading strategies Dimensionality reduction techniques with case studies in portfolio management, trading strategy, and yield curve construction Algorithms and clustering techniques for finding similar objects, with case studies in trading strategies and portfolio management Reinforcement learning models and techniques used for building trading strategies, derivatives hedging, and portfolio management NLP techniques using Python libraries such as NLTK and scikit-learn for transforming text into meaningful representations

Machine Learning from Weak Supervision

Author : Masashi Sugiyama,Han Bao,Takashi Ishida,Nan Lu,Tomoya Sakai
Publisher : MIT Press
Page : 315 pages
File Size : 42,5 Mb
Release : 2022-08-23
Category : Mathematics
ISBN : 9780262370561

Get Book

Machine Learning from Weak Supervision by Masashi Sugiyama,Han Bao,Takashi Ishida,Nan Lu,Tomoya Sakai Pdf

Fundamental theory and practical algorithms of weakly supervised classification, emphasizing an approach based on empirical risk minimization. Standard machine learning techniques require large amounts of labeled data to work well. When we apply machine learning to problems in the physical world, however, it is extremely difficult to collect such quantities of labeled data. In this book Masashi Sugiyama, Han Bao, Takashi Ishida, Nan Lu, Tomoya Sakai and Gang Niu present theory and algorithms for weakly supervised learning, a paradigm of machine learning from weakly labeled data. Emphasizing an approach based on empirical risk minimization and drawing on state-of-the-art research in weakly supervised learning, the book provides both the fundamentals of the field and the advanced mathematical theories underlying them. It can be used as a reference for practitioners and researchers and in the classroom. The book first mathematically formulates classification problems, defines common notations, and reviews various algorithms for supervised binary and multiclass classification. It then explores problems of binary weakly supervised classification, including positive-unlabeled (PU) classification, positive-negative-unlabeled (PNU) classification, and unlabeled-unlabeled (UU) classification. It then turns to multiclass classification, discussing complementary-label (CL) classification and partial-label (PL) classification. Finally, the book addresses more advanced issues, including a family of correction methods to improve the generalization performance of weakly supervised learning and the problem of class-prior estimation.

Information and Communications Security

Author : Debin Gao,Qi Li,Xiaohong Guan,Xiaofeng Liao
Publisher : Springer Nature
Page : 483 pages
File Size : 53,5 Mb
Release : 2021-09-17
Category : Computers
ISBN : 9783030868901

Get Book

Information and Communications Security by Debin Gao,Qi Li,Xiaohong Guan,Xiaofeng Liao Pdf

This two-volume set LNCS 12918 - 12919 constitutes the refereed proceedings of the 23nd International Conference on Information and Communications Security, ICICS 2021, held in Chongqing, China, in September 2021. The 49 revised full papers presented in the book were carefully selected from 182 submissions. The papers in Part I are organized in the following thematic blocks:​ blockchain and federated learning; malware analysis and detection; IoT security; software security; Internet security; data-driven cybersecurity.

Practical Natural Language Processing

Author : Sowmya Vajjala,Bodhisattwa Majumder,Anuj Gupta,Harshit Surana
Publisher : O'Reilly Media
Page : 455 pages
File Size : 42,5 Mb
Release : 2020-06-17
Category : Computers
ISBN : 9781492054023

Get Book

Practical Natural Language Processing by Sowmya Vajjala,Bodhisattwa Majumder,Anuj Gupta,Harshit Surana Pdf

Many books and courses tackle natural language processing (NLP) problems with toy use cases and well-defined datasets. But if you want to build, iterate, and scale NLP systems in a business setting and tailor them for particular industry verticals, this is your guide. Software engineers and data scientists will learn how to navigate the maze of options available at each step of the journey. Through the course of the book, authors Sowmya Vajjala, Bodhisattwa Majumder, Anuj Gupta, and Harshit Surana will guide you through the process of building real-world NLP solutions embedded in larger product setups. You’ll learn how to adapt your solutions for different industry verticals such as healthcare, social media, and retail. With this book, you’ll: Understand the wide spectrum of problem statements, tasks, and solution approaches within NLP Implement and evaluate different NLP applications using machine learning and deep learning methods Fine-tune your NLP solution based on your business problem and industry vertical Evaluate various algorithms and approaches for NLP product tasks, datasets, and stages Produce software solutions following best practices around release, deployment, and DevOps for NLP systems Understand best practices, opportunities, and the roadmap for NLP from a business and product leader’s perspective

Driven by Data

Author : Paul Bambrick-Santoyo
Publisher : John Wiley & Sons
Page : 298 pages
File Size : 41,8 Mb
Release : 2010-04-12
Category : Education
ISBN : 9780470548745

Get Book

Driven by Data by Paul Bambrick-Santoyo Pdf

Offers a practical guide for improving schools dramatically that will enable all students from all backgrounds to achieve at high levels. Includes assessment forms, an index, and a DVD.

Semi-Supervised Learning

Author : Olivier Chapelle,Bernhard Scholkopf,Alexander Zien
Publisher : MIT Press
Page : 525 pages
File Size : 42,7 Mb
Release : 2010-01-22
Category : Computers
ISBN : 9780262514125

Get Book

Semi-Supervised Learning by Olivier Chapelle,Bernhard Scholkopf,Alexander Zien Pdf

A comprehensive review of an area of machine learning that deals with the use of unlabeled data in classification problems: state-of-the-art algorithms, a taxonomy of the field, applications, benchmark experiments, and directions for future research. In the field of machine learning, semi-supervised learning (SSL) occupies the middle ground, between supervised learning (in which all training examples are labeled) and unsupervised learning (in which no label data are given). Interest in SSL has increased in recent years, particularly because of application domains in which unlabeled data are plentiful, such as images, text, and bioinformatics. This first comprehensive overview of SSL presents state-of-the-art algorithms, a taxonomy of the field, selected applications, benchmark experiments, and perspectives on ongoing and future research.Semi-Supervised Learning first presents the key assumptions and ideas underlying the field: smoothness, cluster or low-density separation, manifold structure, and transduction. The core of the book is the presentation of SSL methods, organized according to algorithmic strategies. After an examination of generative models, the book describes algorithms that implement the low-density separation assumption, graph-based methods, and algorithms that perform two-step learning. The book then discusses SSL applications and offers guidelines for SSL practitioners by analyzing the results of extensive benchmark experiments. Finally, the book looks at interesting directions for SSL research. The book closes with a discussion of the relationship between semi-supervised learning and transduction.

Artificial Intelligence in Finance

Author : Yves Hilpisch
Publisher : "O'Reilly Media, Inc."
Page : 478 pages
File Size : 54,5 Mb
Release : 2020-10-14
Category : Business & Economics
ISBN : 9781492055389

Get Book

Artificial Intelligence in Finance by Yves Hilpisch Pdf

The widespread adoption of AI and machine learning is revolutionizing many industries today. Once these technologies are combined with the programmatic availability of historical and real-time financial data, the financial industry will also change fundamentally. With this practical book, you'll learn how to use AI and machine learning to discover statistical inefficiencies in financial markets and exploit them through algorithmic trading. Author Yves Hilpisch shows practitioners, students, and academics in both finance and data science practical ways to apply machine learning and deep learning algorithms to finance. Thanks to lots of self-contained Python examples, you'll be able to replicate all results and figures presented in the book. In five parts, this guide helps you: Learn central notions and algorithms from AI, including recent breakthroughs on the way to artificial general intelligence (AGI) and superintelligence (SI) Understand why data-driven finance, AI, and machine learning will have a lasting impact on financial theory and practice Apply neural networks and reinforcement learning to discover statistical inefficiencies in financial markets Identify and exploit economic inefficiencies through backtesting and algorithmic trading--the automated execution of trading strategies Understand how AI will influence the competitive dynamics in the financial industry and what the potential emergence of a financial singularity might bring about

Data Mining and Data Warehousing

Author : Parteek Bhatia
Publisher : Cambridge University Press
Page : 513 pages
File Size : 46,9 Mb
Release : 2019-06-27
Category : Computers
ISBN : 9781108727747

Get Book

Data Mining and Data Warehousing by Parteek Bhatia Pdf

Provides a comprehensive textbook covering theory and practical examples for a course on data mining and data warehousing.

Advanced Natural Language Processing with TensorFlow 2

Author : Ashish Bansal
Publisher : Packt Publishing Ltd
Page : 381 pages
File Size : 52,7 Mb
Release : 2021-02-04
Category : Computers
ISBN : 9781800201057

Get Book

Advanced Natural Language Processing with TensorFlow 2 by Ashish Bansal Pdf

One-stop solution for NLP practitioners, ML developers, and data scientists to build effective NLP systems that can perform real-world complicated tasks Key FeaturesApply deep learning algorithms and techniques such as BiLSTMS, CRFs, BPE and more using TensorFlow 2Explore applications like text generation, summarization, weakly supervised labelling and moreRead cutting edge material with seminal papers provided in the GitHub repository with full working codeBook Description Recently, there have been tremendous advances in NLP, and we are now moving from research labs into practical applications. This book comes with a perfect blend of both the theoretical and practical aspects of trending and complex NLP techniques. The book is focused on innovative applications in the field of NLP, language generation, and dialogue systems. It helps you apply the concepts of pre-processing text using techniques such as tokenization, parts of speech tagging, and lemmatization using popular libraries such as Stanford NLP and SpaCy. You will build Named Entity Recognition (NER) from scratch using Conditional Random Fields and Viterbi Decoding on top of RNNs. The book covers key emerging areas such as generating text for use in sentence completion and text summarization, bridging images and text by generating captions for images, and managing dialogue aspects of chatbots. You will learn how to apply transfer learning and fine-tuning using TensorFlow 2. Further, it covers practical techniques that can simplify the labelling of textual data. The book also has a working code that is adaptable to your use cases for each tech piece. By the end of the book, you will have an advanced knowledge of the tools, techniques and deep learning architecture used to solve complex NLP problems. What you will learnGrasp important pre-steps in building NLP applications like POS taggingUse transfer and weakly supervised learning using libraries like SnorkelDo sentiment analysis using BERTApply encoder-decoder NN architectures and beam search for summarizing textsUse Transformer models with attention to bring images and text togetherBuild apps that generate captions and answer questions about images using custom TransformersUse advanced TensorFlow techniques like learning rate annealing, custom layers, and custom loss functions to build the latest DeepNLP modelsWho this book is for This is not an introductory book and assumes the reader is familiar with basics of NLP and has fundamental Python skills, as well as basic knowledge of machine learning and undergraduate-level calculus and linear algebra. The readers who can benefit the most from this book include intermediate ML developers who are familiar with the basics of supervised learning and deep learning techniques and professionals who already use TensorFlow/Python for purposes such as data science, ML, research, analysis, etc.

Vietnam Telecom Industry Business Opportunities Handbook Volume 1 Strategic, Practical Information, Regulations

Author : IBP, Inc.
Publisher : Lulu.com
Page : 323 pages
File Size : 43,5 Mb
Release : 2019-01-27
Category : Business & Economics
ISBN : 9781438757049

Get Book

Vietnam Telecom Industry Business Opportunities Handbook Volume 1 Strategic, Practical Information, Regulations by IBP, Inc. Pdf

2011 Updated Reprint. Updated Annually. Vietnam Telecommunication Industry Business Opportunities Handbook

Information Processing in Medical Imaging

Author : Alejandro Frangi,Marleen de Bruijne,Demian Wassermann,Nassir Navab
Publisher : Springer Nature
Page : 836 pages
File Size : 54,9 Mb
Release : 2023-06-07
Category : Computers
ISBN : 9783031340482

Get Book

Information Processing in Medical Imaging by Alejandro Frangi,Marleen de Bruijne,Demian Wassermann,Nassir Navab Pdf

This book constitutes the proceedings of the 28th International Conference on Information Processing in Medical Imaging, IPMI 2023, which took place in San Carlos de Bariloche, Argentina, in June 2023. The 63 full papers presented in this volume were carefully reviewed and selected from 169 submissions. They were organized in topical sections as follows: biomarkers; brain connectomics; computer-aided diagnosis/surgery; domain adaptation; geometric deep learning; groupwise atlasing; harmonization; federated learning; image synthesis; image enhancement; multimodal learning; registration; segmentation; self supervised learning; surface analysis and segmentation.

Social Informatics

Author : Emma Spiro,Yong-Yeol Ahn
Publisher : Springer
Page : 528 pages
File Size : 46,9 Mb
Release : 2016-11-01
Category : Computers
ISBN : 9783319478746

Get Book

Social Informatics by Emma Spiro,Yong-Yeol Ahn Pdf

The two-volume set LNCS 10046 and 10047 constitutes the proceedings of the 8th International Conference on Social Informatics, SocInfo 2016, held in Bellevue, WA, USA, in November 2016. The 33 full papers and 34 poster papers presented in this volume were carefully reviewed and selected from 120 submissions. They are organized in topical sections named: networks, communities, and groups; politics, news, and events; markets, crowds, and consumers; and privacy, health, and well-being.