Chitrasri_P181A10
1. Built a neural network without tuning and got accuracy .597
2. Built a neural network with default parameters (clean sweep) in hyper parameter tuning and got accuracy .62
With custom definition script using one layer we got: .638
With parameter range and random sweep got accuracy: .622
3. From hyper parameter tuning with entire grid using 2 hidden layers in auto mode, got an accuracy of 0.643
In this, using parameter range and custom script of 2 hidden layers and in entire grid got accuracy of .637
4. For Recommender system:
• First we change the numeric values of reviews to categorical variables
• Then we select columns in database in the order like: reviewerid, asin, overall in this particular order
• Split the data in recommender mode
• Train the matchbox recommender on number of traits
• Use the test data to score matchbox recommender
• Evaluate recommender
5. Word cloud that came out to be prominent are: can, the, like, just one, will, get, like, etc.