Today's learning :-
- Started with a quick revision of feature selection.
- Tried to understand Wrapper method - OLS(Ordinary Least Squares)one again.
- This time we used 'gretl' tool for model creation and getting summaries.
- In gretl we tried to find profit of 50_startup_companies using OLS
- Also understood how to create visuals using 'gretl' tool
- It is the same example which we have done using python program last day.
- After that switched on DL(Deep Learning), Why we need DL?
- Since traditional ML(Old ML) is great for limited data (features & observation).
- But if we have huge(Big) data in that case traditional ML won't give us accurate results.
- Big Data - Volume, Variety and Velocity(3V's) of data is very high. We have 4V's and 5V's as well.
- Traditional ML is a manual process hence it is always a slow and also there will be chances of mistake. While New ML(DL) quickly select features automatically and help us to get accurate results.
- That's one of the top reason of using DL a lot in NN(Neural Network)
- Then we run a program which not only detect the human face but also recognize it.
- After face recognition used this program to automatically launch 'https://google.com' in web browser, also enabled authentication and run an application.
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