Tasks this week:
Please make sure you are familiar with and understand the relevant concepts commonly used in the mathematical part of machine learning:
1. Advanced Mathematics
1) Function
2) Limit
3) Derivative
4) Extreme value and maximum value
5) Taylor series
6) Gradient
7) Gradient descent
2. Linear Algebra
1) Basic concepts
2) Determinant
3) Matrix
4) Least square method
5) Linear correlation of vectors
3. Probability Theory
1) Event
2) Permutation and combination
3) Probability
4) Bayes' theorem
5) Probability distribution
6) Expectation and variance
7) Parameter estimation
2. This week's video learning content: https://www.bilibili.com/video/BV1Tb411H7uC?p=2
1) P2 probability theory and Bayesian prior
2) P3 matrix and linear algebra
Machine learning is a multi-disciplinary interdisciplinary subject that involves more mathematical knowledge. The knowledge in this lesson has been learned before. This time it will be reorganized according to the key points. We must pay more attention to it. By watching the video, everyone deepened their impression of the basic mathematics of the course.
It is recommended that you take notes while watching, record the main points and the time point, so that you can look back when necessary. Study notes are also part of the assignment.
3. Operation requirements:
1) Paste the video study notes, which require authenticity, do not plagiarize, you can take pictures by handwriting.
2) Summarize "gradient", "gradient descent" and "Bayes' theorem" in your own words. Word editing, mind mapping, handwriting and photo shooting are required, and conciseness and neat layout are required.