Repository files navigation Neural-Networks-Machine-Learning
Notebooks in the area of Neural Networks and Machine learning. All the notebooks in this repo should have an open in colab button at the top of the notebook.
Note not all of these notebooks are finished!
Notebook discussing the basics of gradient descent
Notebook discussing a more in depth example with gradient descent
Notebook going over how to do linear regression using gradient descent by hand
Notebook going over how to do linear regression using Least Squares Method along with using matrix theory and the normal equation
Notebook showing the different packages out there that can do linear regression. There are of course other packages that could do it, but this shows the 3 most popular
Logan's notebook for linear regression
Notebook going over how to do logistic regression using gradient descent by hand
Notebook going over how to do logistic regression using PyTorch
Logan's notebook for logistic regression
A Notebook showing how PCA works using a handmade example
Shows how to do PCA using packages and shows a use case to understand how PCA can be useful
In Depth how to use PyTorch with XOR as an example
Covers what the super position theory is and gives an example
Gives an example of summed impulse response vs np convolve function
An example notebook showing the different types of simulus to a system
Shows an example of different simulus to a first and second order system
shows the differences for the two types of inputs when modeling an input
Convolutional Neural Network
An Introduction notebook to what a Convoluational Neural Network or CNN is
Example of how to code a CNN directly from PyTorch
Another example of how to code a CNN
An Example of how to use a CNN on a time series
Long Short Term Memory Networks
Introduction to what an LSTM is
Advanced example of how to use a LSTM network
An introduction notebook over autoencoders
An example notebook over Variational Autoencoder
Another example notebook over Variational Autoencoder
An introduction notebook over Recurrent networks
An example of how to use a RRN network
An example how to make a gan network
An example how to make a gan network
Notebook over random forest trees
A notebook reviewing those two stats topics
A notebook reviewing those two stats topics
A notebook reviewing covariance
A notebook reviewing maximum likelihood estimation (MLE)
A notebook showing how to generate different distributions and small details about each distribution
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