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Machine Learning

tinyML Talks: Suitability of Forward-Forward and PEPITA Learning to MLCommons-Tiny benchmarks

September 24, 2023 tinyML Benchmarks, forwardforward, Learning, MLCommonsTiny, PEPITA, Suitability, Talks, tinyml

“Suitability of Forward-Forward and PEPITA Learning to MLCommons-Tiny benchmarks” Danilo Pau Technical Director, IEEE, AAIA & ST Fellow System Research

Machine Learning

Machine Learning and Deep Learning in Computational Toxicology (Computational Methods in Engineering & the Sciences)

September 23, 2023 admin Computational, deep, Engineering, Learning, Machine, methods, Sciences, Toxicology

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Machine Learning

Machine Learning for Causal Inference

September 22, 2023 admin Causal, Inference, Learning, Machine

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Machine Learning

Data Mining for Design and Manufacturing: Methods and Applications (Massive Computing, 3)

September 21, 2023 admin Applications, Computing, Data, Design, Manufacturing, Massive, methods, Mining

Used Book in Good Condition

Machine Learning

Prediction and Analysis for Knowledge Representation and Machine Learning: Prediction and Analysis for Knowledge Representation and Machine Learning

September 20, 2023 admin Analysis, Knowledge, Learning, Machine, Prediction, Representation

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Machine Learning

Applications of Optimization and Machine Learning in Image Processing and IoT

September 19, 2023 admin Applications, image, iot, Learning, Machine, Optimization, processing

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Machine Learning

Blockchain, Big Data and Machine Learning

September 18, 2023 admin Big, Blockchain, Data, Learning, Machine

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Machine Learning

Machine Learning and Music Generation

September 17, 2023 admin Generation, Learning, Machine, music

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Machine Learning

A Concise Introduction to Machine Learning (Chapman & Hall/CRC Machine Learning & Pattern Recognition)

September 16, 2023 admin Chapman, Concise, HallCRC, Introduction, Learning, Machine, Pattern, Recognition

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Machine Learning

tinyML Talks: Unsupervised Federated Learning

September 16, 2023 tinyML Federated, Learning, Talks, tinyml, Unsupervised

“Unsupervised Federated Learning” Ranjitha Prasad Assistant Professor IIIT Delhi Modern day applications such as autonomous vehicles, IoT, smart grids, etc.,

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