In this course, you will review the mathematics background required for data science and machine learning. In the first half, we will review linear algebra and statistics. In the second half, we will review probability.
This course is not meant to be a full-length course on linear algebra, statistics and probability. Instead, it focuses on the sub-topics which are relevant for data science and machine learning.
- Linear Algebra: Vectors, Matrices and their properties
- Statistics: Central Tendency metrics, Dispersion and Correlation
- Quiz: Linear Algebra and Statistics
- Probability: Conditional and Marginal Probabilities, and Bayes’ Theorem (Quick Review)
- Probability Distribution (Quick Review)
- Quiz: Probability