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Author: Wee Hyong Tok
Publisher: "O'Reilly Media, Inc."
ISBN: 1492077038
Category : Computers
Languages : en
Pages : 193
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Book Description
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
Author: Wee Hyong Tok
Publisher: "O'Reilly Media, Inc."
ISBN: 1492077038
Category : Computers
Languages : en
Pages : 193
Get Book Here
Book Description
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
Author: Qingshan Liu
Publisher: Springer Nature
ISBN: 9819985374
Category : Computers
Languages : en
Pages : 534
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Book Description
The 13-volume set LNCS 14425-14437 constitutes the refereed proceedings of the 6th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2023, held in Xiamen, China, during October 13–15, 2023. The 532 full papers presented in these volumes were selected from 1420 submissions. The papers have been organized in the following topical sections: Action Recognition, Multi-Modal Information Processing, 3D Vision and Reconstruction, Character Recognition, Fundamental Theory of Computer Vision, Machine Learning, Vision Problems in Robotics, Autonomous Driving, Pattern Classification and Cluster Analysis, Performance Evaluation and Benchmarks, Remote Sensing Image Interpretation, Biometric Recognition, Face Recognition and Pose Recognition, Structural Pattern Recognition, Computational Photography, Sensing and Display Technology, Video Analysis and Understanding, Vision Applications and Systems, Document Analysis and Recognition, Feature Extraction and Feature Selection, Multimedia Analysis and Reasoning, Optimization and Learning methods, Neural Network and Deep Learning, Low-Level Vision and Image Processing, Object Detection, Tracking and Identification, Medical Image Processing and Analysis.
Author: K. Gal
Publisher: IOS Press
ISBN: 164368437X
Category : Computers
Languages : en
Pages : 3328
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Book Description
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.
Author: Shai Avidan
Publisher: Springer Nature
ISBN: 3031197720
Category : Computers
Languages : en
Pages : 801
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Book Description
The 39-volume set, comprising the LNCS books 13661 until 13699, constitutes the refereed proceedings of the 17th European Conference on Computer Vision, ECCV 2022, held in Tel Aviv, Israel, during October 23–27, 2022. The 1645 papers presented in these proceedings were carefully reviewed and selected from a total of 5804 submissions. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation.
Author: Andrew Fitzgibbon
Publisher: Springer
ISBN: 3642337864
Category : Computers
Languages : en
Pages : 508
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Book Description
The seven-volume set comprising LNCS volumes 7572-7578 constitutes the refereed proceedings of the 12th European Conference on Computer Vision, ECCV 2012, held in Florence, Italy, in October 2012. The 408 revised papers presented were carefully reviewed and selected from 1437 submissions. The papers are organized in topical sections on geometry, 2D and 3D shapes, 3D reconstruction, visual recognition and classification, visual features and image matching, visual monitoring: action and activities, models, optimisation, learning, visual tracking and image registration, photometry: lighting and colour, and image segmentation.
Author: Vittorio Ferrari
Publisher: Springer
ISBN: 3030012700
Category : Computers
Languages : en
Pages : 899
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Book Description
The sixteen-volume set comprising the LNCS volumes 11205-11220 constitutes the refereed proceedings of the 15th European Conference on Computer Vision, ECCV 2018, held in Munich, Germany, in September 2018.The 776 revised papers presented were carefully reviewed and selected from 2439 submissions. The papers are organized in topical sections on learning for vision; computational photography; human analysis; human sensing; stereo and reconstruction; optimization; matching and recognition; video attention; and poster sessions.
Author: Hariom Tatsat
Publisher: "O'Reilly Media, Inc."
ISBN: 1492073008
Category : Computers
Languages : en
Pages : 432
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Book Description
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
Author: Björn Andres
Publisher: Springer Nature
ISBN: 3031167880
Category : Computers
Languages : en
Pages : 607
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Book Description
This book constitutes the refereed proceedings of the 44th DAGM German Conference on Pattern Recognition, DAGM GCPR 2022, which was held during September 27 – 30, 2022. The 37 papers presented in this volume were carefully reviewed and selected from 78 submissions. They were organized in topical sections as follows: machine learning methods; unsupervised, semi-supervised and transfer learning; interpretable machine learning; low-level vision and computational photography; motion, pose estimation and tracking; 3D vision and stereo; detection and recognition; language and vision; scene understanding; photogrammetry and remote sensing; pattern recognition in the life and natural sciences; systems and applications.
Author: Jan L. Plass
Publisher: MIT Press
ISBN: 0262356546
Category : Education
Languages : en
Pages : 601
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Book Description
A comprehensive introduction to the latest research and theory on learning and instruction with computer games. This book offers a comprehensive introduction to the latest research on learning and instruction with computer games. Unlike other books on the topic, which emphasize game development or best practices, Handbook of Game-Based Learning is based on empirical findings and grounded in psychological and learning sciences theory. The contributors, all leading researchers in the field, offer a range of perspectives, including cognitive, motivational, affective, and sociocultural. They explore research on whether (and how) computer games can help students learn educational content and academic skills; which game features (including feedback, incentives, adaptivity, narrative theme, and game mechanics) can improve the instructional effectiveness of these games; and applications, including games for learning in STEM disciplines, for training cognitive skills, for workforce learning, and for assessment. The Handbook offers an indispensable reference both for readers with practical interests in designing or selecting effective game-based learning environments and for scholars who conduct or evaluate research in the field. It can also be used in courses related to play, cognition, motivation, affect, instruction, and technology. Contributors Roger Azevedo, Ryan S. Baker, Daphne Bavelier, Amanda E. Bradbury, Ruth C. Clark, Michele D. Dickey, Hamadi Henderson, Bruce D. Homer, Fengfeng Ke, Younsu Kim, Charles E. Kinzer, Eric Klopfer, James C. Lester, Kristina Loderer, Richard E. Mayer, Bradford W. Mott, Nicholas V. Mudrick, Brian Nelson, Frank Nguyen, V. Elizabeth Owen, Shashank Pawar, Reinhard Pekrun, Jan L. Plass, Charles Raffale, Jonathon Reinhardt, C. Scott Rigby, Jonathan P. Rowe, Richard M. Ryan, Ruth N. Schwartz, Quinnipiac Valerie J. Shute, Randall D. Spain, Constance Steinkuehler, Frankie Tam, Michelle Taub, Meredith Thompson, Steven L. Thorne, A. M. Tsaasan
Author: Long Cheng
Publisher: Springer
ISBN: 303004212X
Category : Computers
Languages : en
Pages : 716
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Book Description
The seven-volume set of LNCS 11301-11307, constitutes the proceedings of the 25th International Conference on Neural Information Processing, ICONIP 2018, held in Siem Reap, Cambodia, in December 2018. The 401 full papers presented were carefully reviewed and selected from 575 submissions. The papers address the emerging topics of theoretical research, empirical studies, and applications of neural information processing techniques across different domains. The 4th volume, LNCS 11304, is organized in topical sections on feature selection, clustering, classification, and detection.
