Difference Between ML and Data Mining

Data is everywhere, NEWS : we have come across news like Big companies expanding their data warehouse eg — Google on Feb 2020 pledged to invest 11B USD to expand their data-center.

We often confuse with ML and Data Mining, like when to use what ?Let’s us take a problem to understand when to use what?

Problem statement — Find the best location in your neighborhood to start a Barbeque Nation.

Here we need to understand the business problem first, right place to start Barbeque Nation to maximize the profit.

Let’s analyze

1. Location with dense teen population
2. Location with car parking
3. Close proximity to veg markets
4. Easy available labors near by

Like wise there many factors which corresponds to max the profitability of our business. Data base comprises of all the past successful and failure Barbeque Nation is give to us, As engineer let’s analyze, and find the solution.

Implementing Data Mining technique to solve the problem:

Datamining is all about finding hidden pattern or sequence form the data to provide insights about business to whose who need it.

Where as Machine Learning is all about teaching the machine to understand and predict or to preform action based on the environment , here training is given to the machine in order to learn the pattern and sequence. Here no human intervention is needed.

Coming to our problem, we have the data and need to find the combination of the features which results in max profit. Here we can use Datamining to solve this problem because we have the data and we just need to find combination of factors which corresponds to max profit for our next venture.

So when to use ML here , when we need to predict profit based on the factors let’s say like holiday and profit level . Then we can use ML in this problem.