Mathematics-for-Machine-Learning-and-Data-Science-Specialization-Coursera
ML-foundations
| Mathematics-for-Machine-Learning-and-Data-Science-Specialization-Coursera | ML-foundations | |
|---|---|---|
| 4 | 1 | |
| 290 | 2,984 | |
| - | - | |
| 6.3 | 5.4 | |
| 11 months ago | 21 days ago | |
| Jupyter Notebook | Jupyter Notebook | |
| - | MIT License |
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Mathematics-for-Machine-Learning-and-Data-Science-Specialization-Coursera
ML-foundations
-
Worried about Calculus
As others have said, you won't need calculus immediately, but it's important that you make a good attempt at learning up to Calc3. I also didn't have a math heavy undergrad so it took a lot of self-study for me, but it's possible. Simulation has a great math boot camp at the beginning to review everything but you'll want to be prepped with Calc before that because that class is all calculus based probability. Some other good resources are the 3Blue1Brown videos on YouTube. They have a great series for both calc & linear algebra to talk through all the intuition with visuals. I also really like John Krohns series because you code through the math which is very applicable for us in this program. I only did his linear Algebra, but he has a whole series with Calc and probability, too. https://github.com/jonkrohn/ML-foundations
What are some alternatives?
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Andrew-NG-Notes - This is Andrew NG Coursera Handwritten Notes.
ITC - Computer Science coursework and projects at Tec de Monterrey 👨🎓
coursera-deep-learning-specialization - Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models
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