The elements of statistical learning : data mining, inference, and prediction /

Introduction to semi-supervised learning /
by: Zhu, Xiaojin, Ph. D.
Published: (2009)

Semi-supervised learning /
Published: (2006)

Supervised learning : mathematical foundations and real-world applications /
by: Chakrabarty, Dalia
Published: (2025)

Machine learning from weak supervision : an empirical risk minimization approach /
by: Sugiyama, Masashi, 1974-
Published: (2022)

Types of supervised machine learning.
Published: (2019)

What is supervised machine learning?.
Published: (2019)

Semi-supervised learning /
Published: (2006)

Learn about sentiment analysis with supervised learning in R with data from the Economic News Article Tone dataset (2016) /
by: Shi, Feng, active 2019
Published: (2019)

Graph-based semi-supervised learning /
by: Subramanya, Amarnag, et al.
Published: (2014)

Multi-label dimensionality reduction /
by: Sun, Liang, et al.
Published: (2014)

Boosting : foundations and algorithms /
by: Schapire, Robert E.
Published: (2012)

Implementation and Interpretation of Machine and Deep Learning to Applied Subsurface Geological Problems : Prediction Models Exploiting Well-Log Information.
by: Wood, David A. (Petroleum engineer)
Published: (2025)

Learn about sentiment analysis with supervised learning in Python with data from the Economic News Article Tone dataset (2016) /
by: Shi, Feng
Published: (2019)

The mathematics of generalization : the proceedings of the SFI/CNLS Workshop on Formal Approaches to Supervised Learning /
Published: (1995)

Supervised learning in remote sensing and geospatial science : theory and practice /
by: Maxwell, Aaron E., et al.
Published: (2025)

Machine learning & predictive modelling for recommendations & insight : Mallzee.
Published: (2019)

Learning to rank for information retrieval and natural language processing /
by: Li, Hang, 1965-
Published: (2011)

Elements of machine learning /
by: Langley, Pat
Published: (1996)

Embracing the value of data in broadcasting : Channel 4.
Published: (2019)

Deep learning : crash course 2023.
Published: (2023)

Federated learning : from algorithms to system implementation /
by: Bo, Liefeng
Published: (2025)

Beginning Deep Learning with TensorFlow : Work with Keras, MNIST Data Sets, and Advanced Neural Networks /
by: Long, Liangqu, et al.
Published: (2022)

Scalable and distributed machine learning and deep learning patterns /
Published: (2023)

Conformal prediction for reliable machine learning : theory, adaptations, and applications /
Published: (2014)

End-to-end deep learning for predicting Airbnb prices /
Published: (2020)

Deterministic and statistical methods in machine learning : first international workshop, Sheffield, UK, September 7-10, 2004 : revised lectures /
Published: (2005)

Machine learning applications : from computer vision to robotics /
Published: (2024)

Learning, networks and statistics /
Published: (1997)

Deep learning : from algorithmic essence to industrial practice /
by: Wang, Shuhao, et al.
Published: (2025)

Deep learning for data analytics : foundations, biomedical applications, and challenges /
Published: (2020)

Explainable deep learning AI : methods and challenges /
Published: (2023)

Why machines learn : the elegant math behind modern AI /
by: Ananthaswamy, Anil
Published: (2024)

Deep learning : a practical introduction /
by: Martinez-Ramón, Manel, et al.
Published: (2024)

Dive into deep learning /
by: Zhang, Aston, et al.
Published: (2024)

Understanding deep learning /
by: Prince, Simon J. D. (Simon Jeremy Damion), 1972-
Published: (2023)

The science of deep learning /
by: Drori, Iddo
Published: (2023)