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marktechpost1y
Deep Learning Architectures From CNN, RNN, GAN, and Transformers To Encoder-Decoder Architectures
GANs are an innovative class of AI algorithms used in unsupervised machine learning, implemented by two neural ... which the decoder then uses to produce the output. This architecture is common in ...
InfoWorld6y
What is deep learning? Algorithms that mimic the human brain
In most discussions, deep learning means using deep neural networks. There are, however, a few algorithms that implement ... intermediate layers. In recurrent neural networks, neurons can ...
GitHub1y
Hands-On Deep Learning Algorithms with Python
What is this book about? Deep learning is one of the most popular domains in the AI space, allowing you to develop multi-layered models of varying complexities. This book covers the following exciting ...
GitHub11d
TheKidPadra/DeepLearning.AI-Deep-Learning-Specialization
The Deep Learning Specialization is a foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the ...
IEEE6y
Review of Deep Learning Algorithms and Architectures
Deep neural network (DNN) uses multiple (deep) layers of units with highly optimized algorithms and architectures ... deep residual networks, recurrent neural networks, reinforcement learning, ...
IEEE4mon
Comparative study of Neural Architecture Search methods: Random Search, RNN + Reinforcement Learning, and Evolutionary Algorithms on CIFAR-10
Abstract: In the past few years, Neural Architecture Search (NAS ... Random Search, RNN + RL (Recurrent Neural Networks and Reinforcement Learning based method), and the Evolutionary Algorithm ...
Frontiers1y
Predicting groundwater level using traditional and deep machine learning algorithms
This research aims to evaluate various traditional or deep machine learning ... The diagram depicted in Figure 1 illustrates the prediction procedure for GWL employing both traditional and deep ML ...