René's URL Explorer Experiment


Title: Intro to Deep Learning

Description: Deep Learning Tutorial using Keras

direct link

Domain: kitchell.github.io

authorLindsey M Kitchell

Links:

1. Intro to Deep Learninghttps://kitchell.github.io/DeepLearningTutorial/1introtodeeplearning.html
2. Intro to Kerashttps://kitchell.github.io/DeepLearningTutorial/2introtokeras.html
3. MLPs in Kerashttps://kitchell.github.io/DeepLearningTutorial/3mlpsinkeras.html
4. CNNs in Kerashttps://kitchell.github.io/DeepLearningTutorial/4cnnsinkeras.html
5. Activation Functionshttps://kitchell.github.io/DeepLearningTutorial/5activationfunctions.html
6. Other Useful Keras Functionshttps://kitchell.github.io/DeepLearningTutorial/6otherkerasfunctions.html
7. Loss Functions and Optimizershttps://kitchell.github.io/DeepLearningTutorial/7lossfunctionsoptimizers.html
8. Evaluating Neural Networkshttps://kitchell.github.io/DeepLearningTutorial/8evaluatingnns.html
9. Data Preprocessinghttps://kitchell.github.io/DeepLearningTutorial/9datapreprocessing.html
10. Regularizationhttps://kitchell.github.io/DeepLearningTutorial/10regularization.html
11. Hyperparameter Tuninghttps://kitchell.github.io/DeepLearningTutorial/11hyperparametertuning.html
Home (current)https://kitchell.github.io/DeepLearningTutorial/index.html
About the Authorhttps://lindseykitchell.weebly.com/
Keras documentaiton for loss functionshttps://keras.io/losses/
image source is this useful resource on learning rateshttps://towardsdatascience.com/estimating-optimal-learning-rate-for-a-deep-neural-network-ce32f2556ce0
Keras documentation on optimizershttps://keras.io/optimizers/
Nesterov momentum is a different version of the momentum method which has stronger theoretical converge guarantees for convex functions. In practice, it works slightly better than standard momentumhttps://towardsdatascience.com/learning-rate-schedules-and-adaptive-learning-rate-methods-for-deep-learning-2c8f433990d1
learning rate schedulerhttps://keras.io/callbacks/#learningratescheduler
https://medium.com/octavian-ai/which-optimizer-and-learning-rate-should-i-use-for-deep-learning-5acb418f9b2https://medium.com/octavian-ai/which-optimizer-and-learning-rate-should-i-use-for-deep-learning-5acb418f9b2
https://towardsdatascience.com/learning-rate-schedules-and-adaptive-learning-rate-methods-for-deep-learning-2c8f433990d1https://towardsdatascience.com/learning-rate-schedules-and-adaptive-learning-rate-methods-for-deep-learning-2c8f433990d1
http://ruder.io/optimizing-gradient-descent/index.html#gradientdescentoptimizationalgorithmshttp://ruder.io/optimizing-gradient-descent/index.html#gradientdescentoptimizationalgorithms
Evaluating the Neural Networks (cross validation)https://kitchell.github.io/DeepLearningTutorial/8evaluatingnns.html

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