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GitHub / johnathanalyst / Coursera-Deep-Learning
A five-course specialization covering the foundations of Deep Learning, from building CNNs, RNNs & LSTMs to choosing model configurations & paramaters like Adam, Dropout, BatchNorm, Xavier/He initialization, and others.
JSON API: https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/johnathanalyst%2FCoursera-Deep-Learning
Stars: 2
Forks: 0
Open Issues: 0
License: other
Language: Jupyter Notebook
Repo Size: 105 MB
Dependencies: pending
Created: about 5 years ago
Updated: 8 months ago
Last pushed: about 5 years ago
Last synced: 8 months ago
Topics: adam-optimizer, batch-normalization, bias-variance, convergence, convolutional-neural-networks, deep-learning, gradient-checking, image-classification, mini-batch-gradient-descent, neural-style-transfer, object-detection, optimization, regularization, residual-networks, rmsprop, yolo