This is the second chapter of a three-part series on Evolutionary Feature Selection with Big datasets. We will start where we left off, namely with a review of existing metaheuristics with special focus on Genetic Algorithms.
Deep learning applications are now truly amazing, ranging from image detection to natural language processing (for example, automatic translation). It gets even more amazing when Deep Learning becomes unsupervised or is able to generate self-representations of the data.
When we want to fit a Machine Learning (ML) model to a big dataset, it is often recommended to carefully pre-process the input data in order to obtain better results.