The Complete Machine Learning Roadmap

ML Engineer here, this roadmap is very solid. If you have a good understanding of the concepts mentioned here, you're 100% ready to take on real-world projects. Good luck to everyone who's on this journey.

when I have roadmap, only thing left is consistency 😅

This video just changed my personality. I’m educated now.

That's a solid roadmap. I'm getting masters in applied CS with a course in machine learning and I learned most things mentioned in this video

Congrats Mosh 4 million students around world from Somalia

40 yo here and my motivation just went 📈 Thank you so much and see you in about 2 years. 🙏

I am doing a AI bachelor degree in Melbourne (Hi, Mosh! lol), currently half way through the whole degree lol. Each semester takes 3 months to finish. Because I got 4 units exempted, I can do 3 units per semester. All the things mentioned in the video really sounds like my whole degree is learning about really. For math, I learnt discrete math, Calculus, and I am going to learn linear algebra next semester. I got Distinction for calculus. Only credit for discrete math. I got hooked on GRAPH THEORY when I was learning discrete math. super hands on knowledge about solving real life problems, like preventing crash in timetables and all that. I just finished data structure and algorithm unit this semester, will get HD for this unit. It was very time consuming but super fun as well. I was forcing myself to translate algorithm to code by myself and if I cannot I ask Claude to guide me and explain from heads to toe, instead of just asking to hand me the code. OH, I also learnt Computational intelligence this semester, mainly A* search and gain a good understanding about heuristic admissible, like Manhattan distance or Euclidean distance. OH, also, data wrangling which I assume is referring to data handling that Mosh was saying in the video lol. Basically, my whole semester was around pandas and numpy, and some matploylib for plot creating. Well coz I dedicated more time on data structure and algorithm, I did not spend enough time diving into it and will only get credit. hahaha But now I am free, I will work with Claude to training a model to help cluster some info to begin with and get into fraud detection models and all that, and this will hopefully walk myself through the whole process of model training (super facial level) and introduce myself to tools like pytorch and tensorflow. Well, next semester, I will learn about unit, machine learning and linear algebra and a ground project. Next year, I will learn NLP, deep learning, and Computer vision and robotics. --------------------- I would say if you are thinking about enrolling in AI degree, and if you are good at learning mathematics and even have strong math intuition, you should really give AI a try. lol I am from a none coding background and it did take me a year to start to get the around with programming languages like C#. But math is another thing I see lots CS background students struggle with, so even they might have got exposure to programming early on in their life compared to people like me. For example, when we learnt about data complexity, big O, run time all that, it was pretty straight forward to me as it involves some simple limit - L'Hôpital / calculus knowledge and Gaussian sum, but it seemed that lots students did struggle with it. But if you love about learning math, and comfortable with math, and just that you are from none-coding background, just needs exposure and learning and practices to coding and it does take some time, but once overcome, it will multiply lol

pleeeeeeeeeease mosh make a complete tutorial on your channel on machine learning and AI from beginner to advance. We are million of students waiting for such course🙏🙏🙏🙏🙏🙏🙏🙏🙏🙏🙏🙏

My brain just filed this under "elite knowledge."

From a design grad to an AI engineer with no tech degree, I owe it all to YouTube and grit. The secret? Consistency and hustle. If you’ve got that, nothing’s too difficult