Machine Learning can be overwhelming for beginners. The are complicated algorithms, complex mathematical equations, different tools available, and not so well-documented examples to deal with.
What is machine learning anyway?
In the simplest description, it is a science of creating a program to learn from existing data and be able to predict a required output when fed by a new data. It is very exciting field and it is the driving force behind the widespread application of Artificial Intelligence(AI) as we know today.
There’s a lot of application for machine learning. We may not have noticed it but we are encountering them in our daily lives. Examples would be
- The camera in your smartphone detects your face while taking that selfie
- Predicting the weather
- Photo-tagging in your social network page
- Reading the address in a mail envelope for automatic routing
- Safety detectors in your car like lane departure, forward collision, pedestrian detection, etc..
- Self-driving cars
- And the list goes on…
I created a tutorial with complete documentation and working code without the complexities of the algorithm behind machine learning. I hope with this simple guide, you will have a good head start. Check out the code at Github.