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Book review: Christoph Molnar. 2020. Interpretable Machine Learning: A Guide for Making Black Box Models Explainable

Metamorphosis: A Journal of Management Research
Christoph Molnar. 2020. Interpretable Machine Learning: A Guide for Making Black Box Models Explainable, Lulu.com, pp. 318, ₹6690.
R. K. Sinha
semanticscholar   +1 more source

Machine Learning and Ethics

2021
When new technology is introduced into healthcare, novel ethical dilemmas arise in the human-machine interface. As artificial intelligence (AI), machine learning (ML) and big data can exhaust human oversight and memory capacity, this will give rise to many of these new dilemmas.Technology has little if any ethical status but is inevitably interwoven ...
Mathiesen, Tiit, Broekman, Marike
openaire   +3 more sources

Federated Machine Learning

ACM Transactions on Intelligent Systems and Technology, 2019
Today’s artificial intelligence still faces two major challenges. One is that, in most industries, data exists in the form of isolated islands. The other is the strengthening of data privacy and security.
Qiang Yang   +3 more
semanticscholar   +1 more source

Learning molecular machines by machine learning

Eurasian Journal of Science Engineering and Technology
Proteins, often referred to as molecular machines, are essential biomolecules that perform a wide range of cellular functions, typically by forming complexes. Understanding their three-dimendional (3D) structures is key to deciphering their functions.
Rumeysa Hilal Çelik   +3 more
openaire   +1 more source

Do Machine-Learning Machines Learn?

2018
We answer the present paper’s title in the negative. We begin by introducing and characterizing “real learning” (\(\mathcal {RL}\)) in the formal sciences, a phenomenon that has been firmly in place in homes and schools since at least Euclid. The defense of our negative answer pivots on an integration of reductio and proof by cases, and constitutes a ...
Selmer Bringsjord   +3 more
openaire   +1 more source

Machine Learning in Medicine

New England Journal of Medicine, 2019
Machine Learning in Medicine In this view of the future of medicine, patient–provider interactions are informed and supported by massive amounts of data from interactions with similar patients.
Alvin Rajkomar   +2 more
openaire   +2 more sources

Machine Learning: A Survey

1997
Intelligence and learning are intimately connected. They need each other to be at their peak. This is why, since its inception in the fifties, Artificial Intelligence has been preoccupied with the study of learning, as testified by the pioneering works devoted to the first cybernetic" turtles" or" mouses", or the CHECKERS program [1].
Cornuéjols, Antoine, Moulet, Marjorie
openaire   +2 more sources

Events and Machine Learning

Topics in Cognitive Science, 2020
Hebblewhite, Hohwy, and Drummond view the special issue from a machine learning perspective drawing close relations to model‐based, hierarchical reinforcement learning.
Augustus Hebblewhite   +2 more
openaire   +3 more sources

Machine Learning: The Ghost in the Learning Machine

2009
Since ancient time learning has played a significant role in building the basis of human intelligence. The tendency for learning with the increased dynamics and complexity of the global economy is growing. If in the past most of the learning efforts were concentrated in high-school and college years, in the 21st century learning becomes a continuous ...
openaire   +1 more source

Foundations of Machine Learning

Introduction to AI Techniques for Renewable Energy Systems, 2021
N. Nathani, Abhishek Singh
semanticscholar   +1 more source

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