This repository consists of Deep Learning Projects i'll be working on for the next month.
Udemy's Deep Learning A-Z Course Begins ! And this are the projects and my work progress throughout...
The First step and the most basic step for any Machine Learning / Deep Learning Code is the Preprocessing Step ! Preprocessing Step includes importing Libraries, reading from the csv files, dividing into testing and Training sets, Dealing with the missing data, encoding the categorial data and Feature Scaling.
Once done with the Preprocessing step, things change a bit. Different Algorithms use the training data differently to learn from it.
Machine Learning Algorithms just learn from the Training data into a general manner by taking all the entries together and scaling in to one of the algorithms and then coming up with the hypothesis (Function) which is a generalized version of what they have learned and using that hypothesis to predict.
Deep Learning, on the other hand, are much more dynamic, not only do they Learn from the algorithms but also they have this special Feature called BACKTRACKING, which is the heart of an Deep Learning Algorithm.
The general template of any Classification step would consists of Making object of a classifier, fitting the training data, let the Machine learn, then provide it some data to predict and then Plot and viewing the results.
PS : For more info on the Code. Read through Wiki !