Chances are you got enchanted by a limitless virtual assistant capable of performing every little task you were lazy to pull off in movies like Iron Man, Westworld, Silicon Valley, and a plethora of others. Or the Artificial Intelligence hype has also affected you. Like me, you understand that must move fast or risk staying behind. But there is one problem. Where do I begin?
Luckily, you have one of mankind's greatest inventions on the go: The internet. In the search box, you type in "How to create an Artificial Intelligence."
Someway somehow through your research, you discover a subdomain called Machine learning which is one of the backbones behind Artificial Intelligence. Now it becomes your mission to achieve mastery in this subdomain. As a result, you return to google.com and type Machine learning tutorials. This simple google search hurls you into a plethora of machine learning information. Subsequently, you end up deep in the maze I call "Tutorial Hell."
Lucky for you, I went down this rabbit hole and made what experts say is a 6month journey last into about a year or two.
Here is my Guide To Studying Machine learning from scratch with no prior experience.
A major problem I witness people who love machine learning make is to study every little detail about the python programming language. This is wrong unless you desire to be a python developer, in which case you do not because you are reading this guide. I would advise once you learn the basics loops, dictionaries, reading and writing in files, and all the OOP concepts.
Take the Stanford Machine learning course on Coursera. I anticipate a lot of hostility to this advice especially from people who want to start solving machine learning problems on sites like Kaggle. I admit the course may be old, but then the level of theoretical knowledge you as a beginner will gain is almost unrivaled.
If you finish this course, well done. Now you are ready to practice and learn simultaneously well not yet. Right now, the next thing to do is go on Kaggle.com and take the pandas, numpy, intro to ML, intermediate ML, data cleaning, feature engineering courses. This should take about a week or two. Another playlist I would recommend is to use Kraish Naik's Youtube videos side by side with your machine learning course.
The best way to truly hone your skills is through a lot of machine learning competitions. I will leave links to various machine learning competitions you must try your hands on in the link below