Here is a new corona dashboard:

https://covid19.arthought.com/

Probably the most interesting story is the large disparity of the national death rate. For instance Germany has a much lower death rate than Italy.

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# Category archives: Software

## Corona dashboard

## Audio compression via images

## Matrix operations with pytorch – optimizer – addendum

## Matrix operations with pytorch – optimizer – part 3

## Matrix operations with pytorch – optimizer – part 2

## Matrix operations with pytorch – optimizer – part 1

## Comparison of a very simple regression in pytorch vs tensorflow and keras

## Colab, MLflow and papermill

## Loss surface with multiple valleys

## Comparison of a very simple regression in tensorflow and keras

“The first duty in life is to be as artificial as possible. What the second duty is no one has as yet discovered.” Oscar Wilde

Here is a new corona dashboard:

https://covid19.arthought.com/

Probably the most interesting story is the large disparity of the national death rate. For instance Germany has a much lower death rate than Italy.

In this post we will use an image compression technique to compress audio signals. We start with a few highlights, screenshots and audio snippets.

This blog post is an addendum to a 3 post miniseries1. Here were present 2 notebooks. 02a—SVD-with-pytorch-optimizer-SGD.ipynb Is a dropin replacement of the stochastic gradient + momentum method shown earlier2, but with using the inbuilt pytorch sgd optimiser. 02b—SVD-with-pytorch-optimizer-adam.ipynb Uses the inbuild pytorch adam optimizer – rather than the sgd optimiser. As known in the […]

SVD with pytorch optimizer This blog post is part of a 3 post miniseries. Today’s post in particular covers the topic SVD with pytorch optimizer. The point of the entire miniseries is to reproduce matrix operations such as matrix inverse and svd using pytorch’s automatic differentiation capability. These algorithms are already implemented in pytorch itself […]

pytorch – matrix inverse with pytorch optimizer This blog post is part of a 3 post miniseries. Today’s post in particular covers the topic pytorch – matrix inverse with pytorch optimizer. The point of the entire miniseries is to reproduce matrix operations such as matrix inverse and svd using pytorch’s automatic differentiation capability. These algorithms […]

pytorch – playing with tensors This blog post is part of a 3 post miniseries. The point of the entire miniseries is to reproduce matrix operations such as matrix inverse and svd using pytorch’s automatic differentiation capability. These algorithms are already implemented in pytorch itself and other libraries such as scikit-learn. However, we will solve […]

This is an follow up to https://arthought.com/comparison-of-a-very-simple-regression-in-tensorflow-and-keras/ It covers the same topic but in pytorch.

Machine learning with the maximum of free GPU currently available plus the ability to keep a neat log of your data science experiments. Interested? My article shows a deep dive solution. Quick summary Colab, MLflow and papermill are individually great. Together they form a dream team. Colab is great for running notebooks, MLflow keeps records […]

This post is a follow-up of 1. We start off with an eye-catching plot, representing the functioning of an optimiser using the stochastic gradient method. The plot is explained in more detail further below. Visualisation of a loss surface with multiple minima. The surface is in gray, the exemplary path taken by the optimiser is […]

In this short post we perform a comparative analysis of a very simple regression problem in tensorflow and keras. We start off with an eye-catching plot, representing the functioning of an optimizer using the stochastic gradient method. The plot is explained in more detail further below. A 3 rotatable version of the Loss function […]