Reference no: EM133729924

Question: Use Kaggle, or the UC Irvine Machine Learning Repository, or a similar machine learning data repository, to research a goal, problem or task that could be solved using:

Supervised machine learning; with
A dataset that can be captured within a .csv file or similar that you are able to source; and with
A simple machine learning algorithm (one of the algorithms that you explored during Week 2)
In your application to SAINT, you will describe:

The goal, problem or task
The kind of data that will be used to train the machine
A training dataset (either as a file, or a link to a dataset)
The features that will be explored in the training
The learning algorithm(s) that could be used to learn from the training data
One or more working models trained on the dataset
Supervised Machine Learning Project
Upload three files:

A document (e.g. Word, PDF) of approximately 500 words that includes:
A description of the goal, problem or task that you want to solve
An explanation of how this goal, problem or task could be framed as a classification or regression task
A training dataset that you will use to address this goal/problem/task - either link to an actual dataset, or provide an appropriate file
An explanation of this dataset - the features included, the target variable, and how the data relates to the classification or regression task
Any modifications or pre-processing you did for this training data, and why
The machine learning algorithms you used for the goal/problem/task, and why
Any hyperparameters you specified for your machine learning models
What you achieved with the model - describe the predictions the model made on a small sample of data

The Orange project (this will be a .ows file).

The model itself (this will be a .pkcls file). If you train more than one model, provide a separate model file for each model.

Note: In addition to the above three files, you need to provide the training data that you use in your project.