Lesson 2: Introduction to Neural Networks_I

Udacity: Intro to Deep Learning with PyTorch:

Day 21 of #60daysofudacity: 

Lesson 2: Introduction to Neural Networks

– Why “Neural Networks”?
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– Perceptron Algorithm

  Screen Shot 2019-07-20 at 10.53.36 PMScreen Shot 2019-07-20 at 10.53.51 PM

– Error Function

An error function is simply something that tells us how far we are from the solution

– Log-loss Error Function

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– Discrete vs Continuous PredictionsScreen Shot 2019-07-21 at 11.24.42 PM

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Day 22 of #60daysofudacity: 

– The Softmax Function

softmax function, which is the equivalent of the sigmoid activation function, but when the problem has 3 or more classes.

Screen Shot 2019-07-21 at 11.28.57 PMScreen Shot 2019-07-21 at 11.29.51 PMScreen Shot 2019-07-21 at 11.32.42 PM

– One-Hot Encoding

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Day 23 of #60daysofudacity: 

– Maximum Likelihood

Cross-Entropy

There’s definitely a connection between probabilities and error functions, and it’s called Cross-Entropy. This concept is tremendously popular in many fields, including Machine Learning. Screen Shot 2019-07-23 at 11.01.59 PMScreen Shot 2019-07-23 at 11.05.47 PMScreen Shot 2019-07-23 at 11.08.50 PMScreen Shot 2019-07-23 at 11.08.56 PM

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