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In general, a learning problem considers a set of n samples of data and then tries to predict properties of unknown data. If each sample is more than a single number and, for instance, a multi-dimensional entry (aka multivariate data), it is said to have several attributes or features. Learning problems fall into a few categories: supervised lea…
🎈 My implementation of the classic fifteen-puzzle-game which consists of 4x4 grid with 15 tiles numbered from 1 to 15. Tiles are moved to order the numbers...
This repository consists a set of Jupyter Notebooks with a different Deep Learning methods applied. Each notebook gives walkthrough from scratch to the end results visualization hierarchically. The Deep Learning methods include Multiperceptron layers, CNN, GAN, Autoencoders, Sequential and Non-Sequential deep learning models. The fields applied …
Hey There Folks In this project, I l learned how to preprocess and merge datasets to calculate needed measures and prepare them for an Analysis. In this project, I worked with the COVID-19 dataset, published by,JOHN HOPKINS UNIVERSITY which consists of the data related to the cumulative number of confirmed cases, per day, in each Country. Also, …