Becoming a data scientist is intrinsically linked to being upto date on statistics and the underlying math along with other practical skills. But how much math do you need? And how do you actually pick up the math? Here is a brief video on learning the math for ML.
What Math is required for ML
The three basic math topics required to get a deeper understanding of Machine Learining are
- Linear Algebra
- Probability and Statistics
- Calculus and Optimization
Resources and Online Courses for learning Math for Machine Learning
Khan academy has a great course on probability and statistics. Very elaborate and intuitive explanation of concepts.
https://www.khanacademy.org/math/statistics-probability
Here is a coursera specialization that covers all of Linear Algebra, probability & statistics and optimization.
https://www.coursera.org/specializations/mathematics-for-data-science
Another coursera specialization that covers linear algebra mostly and a bit of optimization.
https://www.coursera.org/specializations/mathematics-machine-learning
