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1. Different types of learning
Let's start by recalling how supervised learning compares with other forms of machine learning and data processing. We generally distinguish three forms of machine learning: supervised learning, reinforcement learning and unsupervised learning.
Supervised learning involves learning a function f:x→y = f(x) from a database consisting of a large number of example pairs (x
i
,y
i
). The development of deep learning, i.e. software using multi-layer neural networks, has enabled this form of learning to achieve spectacular success in recent years in image analysis, speech recognition and natural language processing
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Different types of learning
Clustering (or partitioning)
Bibliography
Software tools
For computations that do not involve deep learning and that deal with data volumes that do not require the use of distributed computing, the two reference software tools are scikit-learn and R
The Spark Mlib library adapts the main machine learning algorithms (excluding deep learning) to a distributed environment, enabling the processing of very large volumes of data.
Deep...
Events
Annual conferences :
International Conference on Learning Representations ( https://iclr.cc/ )
Conference on Neural Information Processing Systems ( https://nips.cc/ )
Conference on Computer Vision and...
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