You are already familiar with what machine learning is and what it does. I want to help you get started into machine learning quickly. As I learn machine learning, I’ll try to share it with you here. This is just a brief overview without any code. We’ll go through the code in the upcoming articles.
There are 3 core aspects to care about :
1. Prepare the raw data:
This is the phase where your data is cleaned up and exploratory analysis of data is done. This is where most your time as a machine learning engineer is spent. In general, preparing includes filling up empty cells to train the model, deleting junk values from the source entries and other data wrangling techniques are applied here. A “model” is a system that actually performs the required process. A machine learning model is something that takes in the input data, processes the input data which then will predict the output values from the input. We’ll understand more about a model when we explore more of it.
This is where you understand things like 20% of customers in the business are quitting because they really had a hard time with customer service or Sales in Asia has exploded in the last 3 months after introducing Pokemon go natively in the application. The bottom line is, you derive valuable insights.