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| Image Courtesy: Geeksforgeeks |
Okay! Now you might have doubts, say, “Hey, I am a Mechanical Engineer!” or “I have no background of coding” or a simple “I don’t know where to start with!”. You’re reading the right stuff for the answers.
Things you need to remember:
The branch you belong to doesn’t matter when you want to learn something new. (The person who taught me machine learning basics was a mechanical engineer!)
You can always learn coding, provided you are willing to learn.
The Math, especially statistics which you thought to be useless will play a great part here!(if you don’t, it’s OK.)
Get your roadmap set before you start.
Okay, without wasting time let’s quickly see what Machine Learning is!
What’s Machine Learning?
You might get a lot of complicated definitions on the web. But, let's chop it down. To understand what Machine Learning is, have a look at the picture below.
Still didn’t get it? No worries, watch this video to get some idea before you move forward. Because, it’s always better if you do some homework! ;)
Link: https://www.youtube.com/watch?v=ukzFI9rgwfU
Okay, let’s get started!
Step 1: Learn a Coding Language
This is the step which needs your time and efforts. The enthusiasm you build in this step sets your first foot. Python and R are the most widely used programming languages for Data Science. Although, I personally prefer python as it is an easy-to-learn language and fun too! :)
Online Courses:
https://www.udemy.com/course/complete-python-bootcamp/
https://www.udemy.com/share/101W9O/
Also check the other 9 best courses for python 3 here : https://hackr.io/blog/best-python-courses
Step 2: Sharpen your Basics
Machine learning without mathematics is a skeleton without flesh. It’ll start making sense once you start getting to know what’s happening in the algorithms.
Note: Python has different modules which have built-in functionalities due to which learning math behind the magic feels redundant. For a beginner, you can first learn to use those functionalities and later dig deeper to know how those functionalities work(and for this, you NEED math).
Here’s the link for some online courses to learn Machine Learning:
https://www.coursera.org/learn/machine-learning
https://www.udemy.com/share/101Wci/
https://www.coursera.org/learn/machine-learning-with-python
https://www.coursera.org/professional-certificates/ibm-data-science
Step 3: Learn and apply the basics in small problems
Here, you need to learn to apply the functionalities in your code to solve small problems. Practice. Practice. Practice. You can get dummy datasets in kaggle (link below) to practice. Let unavailability of datasets not be the barrier towards learning.
Link : https://www.kaggle.com/datasets
Step 4: You’re all set to go!
Now, you’re the bird who’s ready to leave the nest. Participate in online competitions. Find problems near you and try finding solutions using your knowledge gained by your hours of efforts and patience.
Step 5: You can now move to learning deep learning
Nope! It doesn’t stop here. Learning is infinite. Machine learning takes a step further to a new branch Deep Learning. It’ll be too complicated if I start blabbering using the technical terms right now. You can always learn it once you’ve completed the above 4 steps.
Here’s the link you gotta check out!
https://www.coursera.org/specializations/deep-learning
https://www.udemy.com/share/101WmQ/
In a nutshell,
You’re never late to start learning something new! Happy Learning :)
References
https://blog.avenuecode.com/your-roadmap-to-a-machine-learning-career
https://medium.com/@thisismetis/roadmap-how-to-learn-machine-learning-in-6-months-7c501889b545
Extras
https://www.udemy.com/share/101W9O/
https://www.benzinga.com/money/best-deep-learning-courses/
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