ML-Projects

1)Data Science Problem Basic Workflow

Basics of Data Science Problem: Problem Formulation(New Technique)
1. Data Exploration
2. Data Cleaning
3. Feature Engineering
4. Modelling
5. Solution

2)How To Choose CNN Architecture

The Questions I tend to ask in this Problem are as following:
1. Number of convolution-subsambling pairs needed?
2. Number of Feature Maps needed?
3. How large a dense layer should be?
4. Dropout to overcome overfitting?

###Movie Recommendation:

1. Item Based Recommendation
2. Content Based Recommendation