Tag: Supervised

Partially Supervised Learning Second IAPR International Workshop, PSL 2013, Nanjing, China, May 13-14, 2013, Revised Selected


Free Download Partially Supervised Learning: Second IAPR International Workshop, PSL 2013, Nanjing, China, May 13-14, 2013, Revised Selected Papers By Gabriel B. P. Costa, Moacir Ponti, Alejandro C. Frery (auth.), Zhi-Hua Zhou, Friedhelm Schwenker (eds.)
2013 | 117 Pages | ISBN: 3642407048 | PDF | 3 MB
This book constitutes the thoroughly refereed revised selected papers from the Second IAPR International Workshop, PSL 2013, held in Nanjing, China, in May 2013. The 10 papers included in this volume were carefully reviewed and selected from 26 submissions. Partially supervised learning is a rapidly evolving area of machine learning. It generalizes many kinds of learning paradigms including supervised and unsupervised learning, semi-supervised learning for classification and regression, transductive learning, semi-supervised clustering, multi-instance learning, weak label learning, policy learning in partially observable environments, etc.

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Fundamentals of Supervised Machine Learning With Applications in Python, R, and Stata (Statistics and Computing)


Free Download Fundamentals of Supervised Machine Learning: With Applications in Python, R, and Stata (Statistics and Computing) by Giovanni Cerulli
English | November 15, 2023 | ISBN: 3031413369 | 420 pages | MOBI | 63 Mb
This book presents the fundamental theoretical notions of supervised machine learning along with a wide range of applications using Python, R, and Stata. It provides a balance between theory and applications and fosters an understanding and awareness of the availability of machine learning methods over different software platforms.

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Supervised and Unsupervised Data Engineering for Multimedia Data (EPUB)


Free Download Supervised and Unsupervised Data Engineering for Multimedia Data
English | 2024 | ISBN: 1119786347 | 372 Pages | EPUB | 7 MB
Supervised and Unsupervised Data Engineering for Multimedia Data presents a groundbreaking exploration into the intricacies of handling multimedia data through the lenses of both supervised and unsupervised data engineering. Authored by a team of accomplished experts in the field, this comprehensive volume serves as a go-to resource for data scientists, computer scientists, and researchers seeking a profound understanding of cutting-edge methodologies.

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Applied Supervised Learning with Python


Free Download Applied Supervised Learning with Python: Use scikit-learn to build predictive models from real-world datasets and prepare yourself for the future of machine learning by Benjamin Johnston, Ishita Mathur
English | April 27, 2019 | ISBN: 1789954924 | 404 pages | MOBI | 17 Mb
Explore the exciting world of machine learning with the fastest growing technology in the world

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