How to Approach Machine Learning Problem

Step 1

Frame Problem / Understand Problem

The very first step anyone need is to articulate your problem by identifying and diving deep into understanding the problem you are solving

It can be a simple Binary Classification or Multi-Class Classification to Object Detection to Regression

Step 2

Collecting Data and Data Preprocessing

The next step is to gather all related data and store them in the right format according to the problem statement

After that Analyze the data and extract insights to make a business decision

Apply basic data preprocessing operations

Step 3

Split the Data and Train the Data

Once you have the data preprocessed and ready for training, split the data into Train and Test set, and then Train the data.

Make sure to wisely choose and apply the ML algorithm to train the data based on the problem statement

Step 4

Evaluate Metric

The most important step is to know how to evaluate the results

We must choose the right evaluation metric according to the problem statement we are solving