Most data scientists soon realize that deep learning models can be unwieldy and often impractical to run on smaller devices…
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Layman’s Introduction to Backpropagation
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Writing and training a simple perceptron to find outAn brief practical introduction to the simple perceptron learning algorithm and using it…
Continue ReadingAttention in RNNs
Attention in RNNsUnderstanding the mechanism with a detailed exampleNir ArbelBlockedUnblockFollowFollowingMar 15Montepulciano ItalyRecurrent Neural Networks (RNNs) have been used successfully for many tasks…
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Continue ReadingSimple Deep Learning (Ft my dog)
Simple Deep Learning (Ft my dog)Isabella GrandicBlockedUnblockFollowFollowingFeb 17If AI was an ice cream sundae, deep Learning would be the sprinkles and…
Continue ReadingBackpropagation for people who are afraid of math
We will go over each expression. When trying to update and optimize the network’s weights, we are trying to find-,…
Continue ReadingHow to Create an Equally, Linearly, and Exponentially Weighted Average of Neural Network Model Weights in Keras
The training process of neural networks is a challenging optimization process that can often fail to converge. This can mean…
Continue ReadingAtari – Solving Games with AI???? (Part 2: Neuroevolution)
If you missed Part 1, or…towardsdatascience.comSimilarly to the above example of the evolutionary algorithm used in the game of Snake,…
Continue ReadingDeconstructing BERT: Distilling 6 Patterns from 100 Million Parameters
Right: attention weights for selected token (“i”)On the left, we can see that the [SEP] token disrupts the next-token attention pattern,…
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