Hello to all, how was your day three?? Comment down fast, first. With my #7daysofml day3.
I hope it was great. Here’s how I discovered the importance of the machine learning toolkit.
Contents
Goals For The Day
Today I decided to raise the bar even higher. These are the topics I wish to cover:
- The process before getting the data
- Getting the data
- Creating a test data set
This much is easily there to take hours alone.
(Spoiler Alert: I am gonna know it is more than I thought later)
Challenges For The Day
Today was a lot more challenging.
The first, challenge was understanding the pipeline of data processing.
The second was understanding RMSE and MAE.
For the first time, I felt I was not good enough at statistics.
Last but not least dealing with the bombardment of Python libraries. Although I had used a lot of them before it still felt difficult with a few.
I don’t think this challenge is gonna be as easy as I thought.
Machine learning is much more than basic statistics.
Some Insights I Gained Today: Machine Learning Toolkit Is A Must
I learned a lot of things today. Machine learning cannot be aced without its toolkit.
By machine learning toolkit, I mean statistics and some important python libraries.
When I was first exploring the machine learning toolkit I thought I should learn that along with doing the project.
But I guess one at least needs a basic grip over this machine learning toolkit before diving into machine learning.
That gives me a new challenge for the next seven days which I would start a few days after this one ends.
I would get to know the exact toolkit and will learn that one step at a time taking apt intervals.
How does this idea sound?? Do let me know in the comments below👇
