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https://nptel.ac.in/. The National Programme on Technology Enhanced Learning (NPTEL) is an Indian e-learning platform for university-level science, technology, engineering, and mathematics (STEM) subjects. NPTEL is the largest e-repository in the world of courses in engineering, basic sciences and selected humanities and management subjects. [1]
Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions. [1] Recently, artificial neural networks have been able to surpass many previous approaches in ...
[25] [26] Another class of model-free deep reinforcement learning algorithms rely on dynamic programming, inspired by temporal difference learning and Q-learning. In discrete action spaces, these algorithms usually learn a neural network Q-function Q ( s , a ) {\displaystyle Q(s,a)} that estimates the future returns taking action a ...
Federated learning (also known as collaborative learning) is a sub-field of machine learning focusing on settings in which multiple entities (often referred to as clients) collaboratively train a model while ensuring that their data remains decentralized. [1] This stands in contrast to machine learning settings in which data is centrally stored ...
Online learning is a common technique used in areas of machine learning where it is computationally infeasible to train over the entire dataset, requiring the need of out-of-core algorithms. It is also used in situations where it is necessary for the algorithm to dynamically adapt to new patterns in the data, or when the data itself is ...
v. t. e. In machine learning, a neural network (also artificial neural network or neural net, abbreviated ANN or NN) is a model inspired by the structure and function of biological neural networks in animal brains. [ 1 ][ 2 ] An ANN consists of connected units or nodes called artificial neurons, which loosely model the neurons in the brain.
Bayesian methods are introduced for probabilistic inference in machine learning. [1] 1970s 'AI winter' caused by pessimism about machine learning effectiveness. 1980s: Rediscovery of backpropagation causes a resurgence in machine learning research. 1990s: Work on Machine learning shifts from a knowledge-driven approach to a data-driven approach.
Statistical learning theory is a framework for machine learning drawing from the fields of statistics and functional analysis. [1][2][3] Statistical learning theory deals with the statistical inference problem of finding a predictive function based on data. Statistical learning theory has led to successful applications in fields such as ...