Skip to content

Latest commit

 

History

History
23 lines (12 loc) · 899 Bytes

readme.md

File metadata and controls

23 lines (12 loc) · 899 Bytes

Intelligent Systems Mini-Projects

  • w1: Kaggle Challenge House Sale Prices.

Linear Regression Was used, Rmsl = 0.14394, An example of Linear Regression from Scratch was develop in myregression.py

  • w2: Sentiment analysis of Movie Reviews

Given the dataset at:

[Source: http://ai.stanford.edu/~amaas/data/sentiment/]

Classification if a review is positive or negative using Logistic Regression.

An example of Logistic Regression from Scratch was develop in mylogisticreg.py, to get the maximum likehood, Newton J.Raphson method was used.

  • w3: Sentiment analysis of Movie Reviews

[Source: http://ai.stanford.edu/~amaas/data/sentiment/]

Classification if a review is positive or negative using Logistic Regression.

An example of Back Propagation algorithm from Scratch was develop in Backpropagation.py, to get the maximum likehood, Newton J.Raphson method was used.