Inspiration To Save Doctor's time and giving chance to the needy person who is on the waiting list to make appointments by identifying which person who has already made an appointment will not show up.
What it does Predicts about the person who has made an appointment, that whether he or she will show up at the appointment time or not based on the attributes like Gender, Age, SMS_Received, Diabetes, and Hypertension
How I built it I built it using Jupyter, Python, Google Cloud Product.
Challenges I ran into 1. Out of 15 attributes, identifying which attributes to use for prediction. 2. Some attributes were not in proper format, so to convert them to proper format was a major challenge for me (for example date). 3. I decided to add 1 to 2 new columns based on Scheduled day, spent a lot of time but in the end was not able to use it.
Accomplishments that I'm proud of Attending hackathon for the first time and completing the whole project by myself is one of the proudest things for me. Also, I took this as a real challenge, so I came to know what I know theoretically but not practically. So it showed me where I am in terms of my skills. Also, I used Google Cloud Product and uploaded the whole project there which is also an accomplishment for me. Winning is not important for me but to finish is important.
What I learned I learned a lot about the Google Cloud Platform, how to use it, what products are available from Google. I also came to know that Google Cloud has ML Support and this is the most interesting product for me. I learned some plotting commands in more detail.
What's next for Medical_No_Show To improve the accuracy and to add more data like weather data, traffic data, etc. so that exact reason can be known and could save doctors time and needy people could actually get the change to visit the doctor.
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