Heatmap for a Yolo prediction

Since the R-CNN Object Detection (OD) was released in 2014 until now, deep learning approaches to object detection problems are becoming more and more popular.

OD is now used in almost every field from agriculture to autonomous driving. But one of the main disadvantages of the OD techniques is the lack of interpretability of its outputs that are not human-readable and this is a big concern.

Since that prediction without interpretable explanation will have restricted applicability eventually.

But how can we measure the correctness of an OD model ?

Until recently the only way we could measure how good the outcome of a model is was to evaluate its predictions using a…

Photo by John Schnobrich on Unsplash

Arvato Financial Solutions is a company that provides services that helps other companies through the complexity of credit management since 1961. Nowadays, 7,000 experts are delivering efficient credit management solutions in around 15 countries around the globe.

For the Capstone Project of Udacity Data Science Nanodegree, Arvato Financial Solutions kindly made its data of a real problem available so the students could apply the theory learned to a practical problem.


In this Capstone Project, the goal was to analyze demographics data for customers of a mail-order sales company in Germany, comparing it against demographics information for the general population.



Joe Biden won the election and he is going to be the 46th President of the United States, there are rumours about a second covid-19 wave, the covid-19 vaccines are closer than ever. Reading all those headlines and as a stock market investor a question came to my mind: How does exogenous factors influence the stocks prices?

So as an activity of the Data Science Nanodegree I am taking at Udacity and to try to combine the two things that I love the most that is data analysis and finance I decide to analyse the stock market data, using Data…

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