The new software: Advantages and disadvantages

Recently I published a post about the new software paradigm. The new paradigm of software is the one that the coder does not directly program each of the cases for any of the given inputs. The new paradigm uses training data to let the computer learn the outputs for each input. The computer programs itself […]

The new software: Less coding more data

Software like everything is evolving but it is evolving differently than I thought. When I was studying computer science at the university I thought that the future was parallelism. We were taught only one class in parallel programming. Multi-core computers were on the rise and it seemed to be the thing to learn. Since then […]

Calibration for deep learning models

Wikipedia’s definition for calibration is calibration is the comparison of measurement values delivered by a device under test with those of a calibration standard of known accuracy. Put in a context that means that the distribution of predicted probabilities is similar to the distribution observed probabilities in training data. If we rephrase it again means […]