Kedro is a python data science library that helps with:
creating reproducible, maintainable and modular data science code
How fast is fitting long AR models using Neural prophet?
In this quick test we will fit AR based models with different lags and see how long they take to fit.
In this post I was trying out PyTorch Lightning to see if it’s a library that should be used by default alongside PyTorch.
I will create the same nonlinear probabilistic network from before, but this time using Lightning.
Hence the first few steps are the same as previously shown.
This post follows a similar one I did a while back for Tensorflow Probability:
Linear regression to non linear probabilistic neural network
Is this post we look at season data to compare the playing time of LeBron to other players.
Neural prophet is a time series forecasting library very similar to the Facebook prophet.
Neural prophet runs using pytorch, rather than fbprophet and it’s use of pystan.
It has some potential advantages by using stochastic gradient descent.
This brief post is exploring overfitting neural networks. It comes from reading the paper:
Towards Understanding Generalization of Deep Learning: Perspective of Loss Landscapes
Here we will find some data to see what the state of renewable energy production is within Europe.
The data is collected from:
In this post I will attempt to go over the steps between a simple linear regression
towards a non-linear probabilistic model built with a neural network.
Here we look at fitting a normal distribution to some data using Tensorflow Probability.