Fortunately, Fjodor van Veen from Asimov institute compiled a wonderful #cheatsheet on NN #topologies. If you are not new to Machine Learning, you should have seen it before
via: @cedeeplearning
https://towardsdatascience.com/the-mostly-complete-chart-of-neural-networks-explained-3fb6f2367464
via: @cedeeplearning
https://towardsdatascience.com/the-mostly-complete-chart-of-neural-networks-explained-3fb6f2367464
🔹Machine Learning tips and tricks #cheatsheet
Bias: The #bias of a model is the difference between the expected #prediction and the correct model that we try to predict for given data points.
Variance: The #variance of a model is the variability of the model prediction for given data points.
Bias/variance #tradeoff: The simpler the model, the higher the bias, and the more complex the model, the higher the variance.
from: stanford.edu
via: @cedeeplearning
Bias: The #bias of a model is the difference between the expected #prediction and the correct model that we try to predict for given data points.
Variance: The #variance of a model is the variability of the model prediction for given data points.
Bias/variance #tradeoff: The simpler the model, the higher the bias, and the more complex the model, the higher the variance.
from: stanford.edu
via: @cedeeplearning
🔹Deep Learning #Cheatsheet
Activation function: #Activation functions are used at the end of a hidden unit to introduce #non-linear #complexities to the model. Here are the most common ones
from: stanford.edu
via: @cedeeplearning
Activation function: #Activation functions are used at the end of a hidden unit to introduce #non-linear #complexities to the model. Here are the most common ones
from: stanford.edu
via: @cedeeplearning