Building Deep Learning Model Assessment Answer

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Question :

Only Question

Build a Deep Learning Model for each of the following Problems. 

1. Shopper Purchase Intention: https://archive.ics.uci.edu/ml/datasets/Online+Shoppers+Purchasing+Intention+Dataset

2. CoverType

https://archive.ics.uci.edu/ml/datasets/Covertype

3. Bike Share (Day.csv)

https://archive.ics.uci.edu/ml/datasets/Bike+Sharing+Dataset

 In your solution include the following

  1. All code in R or Python (Notebook required for Python, Recommended for R)
  2. Print first few rows of the training data
  3. Identify the minimum accuracy the model needs to exceed to be of value
  4. Chart of training and validation error and accuracy (or appropriate metric based on problem)
  5. The accuracy(or appropriate metric) of the best model 

Rubric

  1. There are no data processing errors (data types and any pre-processing)
  2. Model is appropriate for the problem (regression, classification etc.)
  3. Metrics are appropriate for the problem
  4. Baseline is identified
  5. Best Model exceeds baseline
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Answer :

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