Handwritten Digit Recognition on MNIST dataset | Python Machine Learning | XGboost

In this hands on lab we will show you how you use XGboost which is a machine learning algorithm. A very popular algorithm which has a very good reputation to Data Scientist especially in competitions in Kaggle.

The following codes are designed to create a machine learning model to determine a number from a database of handwritten numbers from 1 to 9. The data was taken from “THE MNIST DATABASE of handwritten digits”. It has originally 60,000 observations.

The lab will have the follow sections
1: Collecting the data
2: Importing the dataset files from S3
3: Exploratory data analysis
4: Data Cleaning
5: Training the Model
6: Deploying the Model
7: Survival Prediction
8: Delete Endpoints

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