Hello! Machine Learning is not difficult and you dont have to be a math expert. Actually Python provides many libraries which do the complex parts for you. A typical Machine Learning project looks like this:
- Get the data
- Analyze and visualize the data to gain insights.
- Prepare the data.
- Select a model and train it.
- Fine-tune your model
- Maintain your system . 🤖If you want to get started with your first ML project, check out this link:
https://machinelearningmastery.com/machine-learning-in-python-step-by-step/
Also Google offers a free Machine Learning Crash course here:
https://developers.google.com/machine-learning/crash-course/ml-intro
Top comments (9)
Hi Anja,
Isn't
machinelearningmastery.com
a great site! Very good tutorials.Have you seen V. Lavrenko's lectures Or Data Carpentry? Love 'em!
There is so much good content out there...
Hi Matt, yes there are so many great free resources available. :) No I don't know lavenkro and data carpentry, thank you for sharing! 😊🙌
I've published my personal machine learning notebooks a few weeks ago here in DEV. I actually convert all the physical notebooks into Markdown + HTML website. I learn this subject by myself from scratch without frameworks, all practical learning. This subject is not that easy, it was difficult but in the end it worthy.
Yeah, machine learning is a piece of cake.
Hi, at least to use what is there is not difficult. To change the math behind the models to improve them is more complex.
How far is a person going to go if he/She doesn't understand how it works?
That depends on the requirements of the use case. That's also an important skill for developers to learn, knowing how much you need to understand from a code base to be able to use it for your goals.
Thanks for sharing.
You are welcome 😊