We were conducting machine learning classes for past 5 Weeks at maitri every Saturday 6:30 pm
The topics we were covered so far :
1.Machine learning introduction;
* Centrality- mean,mode,median, variance
* Binomial distribution
4.Data prepocessing - consists of testing, validation,training.
Here is our today's session summary:
The mapping of elements from domain to co domain
Our Gokul differentiated continuous and non continuous function with a simple graph, then Arun describes about co-variance and explains how it differ from independent
We concluded the session by discussing on K nearest neighbours and it's drawbacks...
IMPORTANT FORMULAS :
1.F is continuous at x,if
2.variance= summation of 1 to n (x-µ)^2
3. In K nearest neighbours