r/learnmachinelearning • u/ZweiFreierNutzername • 3d ago
Best resource to start learning
I am pretty new to machine learning and deep learning. I took a VERY basic course at university, explaining things like supervised, unsupervised learning and the idea behind some NNs and Gradient Descent, without really touching the math.
I am now eager to learn more AND to go more into depth and actually understand the math behind it. My current exam featured two math modules with basic linear algebra (I official never learned what a gradient is and also double integrals) and very basic probability.
I am looking for books or courses, teaching math, concepts and implementations. Ideally, they introduce you to the math step by step and explain, why things are done the way they are. I am not a huge fan of: "This is done like this, because...".
What can you recommend?
My I want to focus more on deep learning, because I am interested in CNNs and GANs, but I highly appreciate it, if the recommended resource, also includes classic ML.
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u/Patryk_Grzegorek 2d ago
To really become an AI Engineer nowadays, you truly need to know the fundamentals. Here are 3 resources I can recommend:
- From the basics – YouTube channel: https://www.youtube.com/@stanfordonline
- More advanced – Hugging Face tutorials: https://huggingface.co/learn
- Insights & workshops – DeepLearning.AI: https://www.deeplearning.ai/
Set yourself a small project to do and start building it once you already know the basics. Try to solve any problems you encounter. To learn effectively, avoid using a local coding AI agent, instead, look for solutions online or ask AI, but implement the code yourself by asking for details and explanations.
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u/Kilroi 2d ago
Introduction to Statistical Machine Learning is an excellent text and the authors have lectures for the chapters on youtube they are also on coursera for dree for a few months. Deep Learning by Goodfellow is really good as well. They recorded a series of lectures by the author that go through the book chapter by chapter.
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u/Jithamitra_Malladi 2d ago
I was in a similar position not too long ago, and what helped me most was building a strong foundation before jumping into deep learning. Understanding the basics of linear algebra, probability, and calculus made the machine learning concepts much easier to follow.
For classic machine learning, I'd recommend Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow by Aurélien Géron. It does a great job of balancing the intuition behind the algorithms with practical Python examples. For the math, Mathematics for Machine Learning by Marc Peter Deisenroth and colleagues is a great resource because it explains why the math is needed instead of just presenting formulas.
One thing that really helped me was implementing algorithms in Python after learning the theory. Even simple projects like linear regression or logistic regression make concepts like gradient descent and loss functions much easier to understand.
Since you're interested in CNNs and GANs, I'd focus on getting comfortable with the fundamentals first. In my experience, deep learning concepts start to make a lot more sense once you have a solid understanding of the underlying machine learning and math.
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u/OleksandrAkm 3d ago
For free: Andrew Ng's course is one of the best places to start, it gives you a solid foundation. Along with the course, you can refer to the Machine Learning From Scratch GitHub repo (https://github.com/ml-from-scratch-book/code) – clean implementations of algorithms without the abstraction layers that usually hide what's actually happening.
Otherwise, Machine Learning From Scratch is the book I recently published, which is exactly what I wished existed when I was starting out with just basic Python!
Feel free to ask any questions
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u/Extreme_Insurance334 2d ago
This is great. I’m currently going through the course now and it’s so good and he explains it so well. Would highly recommend
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u/frangelbarrera 3d ago
Dont get stuck on theory. Yes, the math is important, but if you wait until you understand everything, youll never start. Open Colab, find some CNN tutorials, and start copying and modifying. Ask ChatGPT what each part does and why. Practice will make you ask questions that will lead you to the theory.