In this podcast I provide a detailed discussion of what is Data Science. In Part 2 I will continue... Follow my podcast: http://anchor.fm/tkorting Subscribe to my YouTube channel: http://youtube.com/tkorting The intro and the final sounds were recorded at my home, using an old clock that belonged to my grandmother. Thanks for listening

Deep Learning articles use benchmarks to measure the quality of the results. However, several benchmarks do not have the copyright of all data used. So, how to believe that every paper uses the same benchmark? From https://www.go-fair.org/fair-principles/ we have the description of the FAIR acronym Findable: The first step in (re)using data is to find them. Metadata and data should be easy to find for both humans and computers.  Accessible: Once the user finds the required data, she/he...

Several authors rely on transfer learning from pretrained models, arguing that using well-known datasets, which are available on the internet (e.g. ImageNet) their model will be able to handle a specific problem with a reduced training step. In Remote Sensing this perspective is also becoming a trend when using Deep Learning techniques to classify Remote Sensing datasets. In my opinion, the datasets used for pretrain are very different from Remote Sensing targets, mainly in two aspects: ...

In this podcast I discuss the (sometimes) wrong use of the term Data Mining, with in accord to the paper From Data Mining to Knowledge Discovery in Databases, written in 1996 by Usama Fayyad, Gregory Shapiro, and Padhraic Smyth,  is defined as: Data mining is a step in the KDD process that consists of applying data analysis and discovery algorithms that produce a particular enumeration of patterns (or models) over the data. KDD means Knowledge Discovery in Databases, and is composed by the...

In this podcast I discuss the wrong use of the term Resolution in scientific articles or in the general media. Resolution in Remote Sensing can be used to describe several aspects of images, such as: temporal resolution: the time difference between two images of the same place spectral resolution: related to the number of bands and wavelengths, such as in Panchromatic, Multispectral, Hyperspectral, or Ultraspectral radiometric resolution: the number of bits needed to store a pixel value...

In this podcast I discuss the extensive use of the Table Strength of Agreement based on different Kappa values, provided by: Landis, J.R. and Koch, G.G., 1977. The measurement of observer agreement for categorical data. Biometrics, pp.159-174. According to Google Scholar, this paper has more than 53.000 citations (up to October, 2019). In my opinion this table has been used sometimes with a different purpose than the original paper, which, according to the authors, "have been illustrated...

In this podcast I discuss the article from Doug Laney, published in 2001, entitled 3D Data Management: Controlling Data Volume, Velocity, and Variety. This paper is one of the basis for the definition of the term "Big Data". Curiously, the explicit term "Big Data" does not appear in the text, but the author explain a 3D interpretation of a database, which grows in Volume, Velocity and Variety, the well known 3 V's. Follow my podcast: http://anchor.fm/tkorting Subscribe to my YouTube...

In this podcast I explain what is an unsupervised classification algorithm and what is a supervised algorithm.  I use examples about remote sensing image classification and I discuss my opinion about the unsupervised algorithms, which are in fact similar to the supervised ones.  Take as one example the well known unsupervised K-Means algorithm. The analyst must inform a priori the most important parameter to run the algorithm, the K value. I have a video about the K-Means...

This is a first message to check if someone will find my podcast and will have interest on it.  Waiting for feedback on remote sensing, image processing, data mining, deep learning, data augmentation, sample selection, articles, papers, etc. Follow my podcast: http://anchor.fm/tkorting Subscribe to my YouTube channel: http://youtube.com/tkorting Thanks for listening