Where Can I Start with Self-Learning Math for Data Science and Machine Learning?

In summary, there are several resources available for self-learning math in the context of data science and machine learning. These include online courses such as Khan Academy and Coursera, as well as textbooks and practice problems from websites like Kaggle and DataCamp. It is also recommended to have a strong foundation in basic math concepts such as algebra, calculus, and linear algebra before diving into more advanced topics. Additionally, utilizing online communities and forums can provide valuable support and guidance for self-learners in this field.
  • #1
Saqib Ali
6
0
My passion is the environment, and I want to apply data science and machine learning to climate data. I didn't learn much from my math courses throughout and haven't taken a physics or chemistry course since high school. I want some guidance on how to self-learn math starting from Calculus needed for machine learning over this upcoming winter break and beyond.
 
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  • #2
Saqib Ali said:
My passion is the environment, and I want to apply data science and machine learning to climate data. I didn't learn much from my math courses throughout and haven't taken a physics or chemistry course since high school. I want some guidance on how to self-learn math starting from Calculus needed for machine learning over this upcoming winter break and beyond.
Welcome to the forum from a fellow Ramblin' Wreck.
 
  • #3
phinds said:
Welcome to the forum from a fellow Ramblin' Wreck.
I aspire to do a PhD in CS where I'll apply CS to climate data. I hope someday I can be a professor at a research university. I've done a lot of research at the Ubicomp Lab at Georgia Tech, and I've talked to an Earth and Atmospheric Science professor about doing research with him next semester and over the summer. The problem is that I lack some basic skills in mathematics that are the underpinning of machine learning and data science. I need to brush up on Calculus, Differential Equations, and Probability and Statistics (maybe a little bit of linear algebra and algorithms but those are my strong suits). It can't hurt to also know combinatorics and graph theory especially when we're in a golden age of Neural Nets. To give me more time to grasp the prerequisite material, I'll probably do a research Master's here and then apply to a lot of different programs.
 

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