Problem Statement 🤔🤯

There are a lot of customers on BiosectRx's platform. Whenever they login into the app and view anything, the company gets pings from their mobile phone indicating that they are using the app.
Provided with 4 weeks of sample data : 3 weeks of training data and 1 week of test data.
Training data contains id, gender, age, number of kids the customer has and all the pings that have been received (during the training data period).
The task is to predict how many hours the customers will be online/using the app on a given day.
So the test data contains customer id, and date (during the test data period). The test data also contains the actual online hours, which is what the model should predict.
Root Mean Squared Error (RMSE) must be the metric for evaluation.

My Solution 💡

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Name		Name	Last commit message	Last commit date
Latest commit History 22 Commits
data		data
1_EDA.ipynb		1_EDA.ipynb
2_Data Preparation.ipynb		2_Data Preparation.ipynb
3_EvalML.ipynb		3_EvalML.ipynb
4_AutoViML.ipynb		4_AutoViML.ipynb
5_TPOT.ipynb		5_TPOT.ipynb
6_ANN_with_TPOT.ipynb		6_ANN_with_TPOT.ipynb
README.md		README.md
Solution.pdf		Solution.pdf
test.csv		test.csv
train.csv		train.csv