Skip to content

Latest commit

 

History

History
30 lines (21 loc) · 1.69 KB

File metadata and controls

30 lines (21 loc) · 1.69 KB

ML Algorithms

All the snippets need to be optimized to be made scalable and are only initial implementations of the standard ML algos

Dataset Sources

* [Power Consumption Patterns ] - Not Available ONLINE

This Week TODO:

  • UNIVARIATE and MULTIVARIATE LINEAR REGRESSION(W/WO GRADIENT DESCENT) -- DONE
  • LOGISTIC REGRESSION on first 10 principal components of a dataset to CLASSIFY an Experiemnt as of Physics OR Chemistry -- DONE
  • NEURAL NETS for binary geo-coordinates classification using back propogation -- DONE ** The Architecture of the neural net implemented is shown below ,with two hidden layers and two units in each hidden layer, apart from bias term **
  • SUPPORT VECTOR MACHINES -- 3 dimensional feature set mapped to 180 dimensional feature set where m= #landmarks/#training egs using gaussian kernel
  • K-Means Clustering --DONE
  • Principal Component Analysis (PCA) --DONE
  • Col Filtering --TODO

README will be updated ** very very frequently