Difference between revisions of "Step 3"

From Research management course
Jump to: navigation, search
Line 14: Line 14:
 
# Download the link to your homework [https://forms.gle/MBkcGz6aK3LX8MFy7 here].
 
# Download the link to your homework [https://forms.gle/MBkcGz6aK3LX8MFy7 here].
 
# Also, [https://forms.gle/v6fEGLRWkXJ6UZXi9 Step 2 homework] reminder
 
# Also, [https://forms.gle/v6fEGLRWkXJ6UZXi9 Step 2 homework] reminder
#  
+
# Refresh in your memory the Bayesian Statistics, see either:
Refresh in your memory the Bayesian Statistics, see either:
 
 
## [https://en.wikipedia.org/wiki/Covariance_matrix Covariance Matrix], [https://en.wikipedia.org/wiki/Multivariate_normal_distribution Multivariate Normal Distribution], [https://en.wikipedia.org/wiki/Generalized_linear_model Generalized Linear Model], [https://en.wikipedia.org/wiki/Ridge_regression#Tikhonov_regularization Ridge Regression], [https://en.wikipedia.org/wiki/Bayesian_inference Bayesian inference]
 
## [https://en.wikipedia.org/wiki/Covariance_matrix Covariance Matrix], [https://en.wikipedia.org/wiki/Multivariate_normal_distribution Multivariate Normal Distribution], [https://en.wikipedia.org/wiki/Generalized_linear_model Generalized Linear Model], [https://en.wikipedia.org/wiki/Ridge_regression#Tikhonov_regularization Ridge Regression], [https://en.wikipedia.org/wiki/Bayesian_inference Bayesian inference]
## the book by C.P. Bishop, chapter 1.
+
## the book by C.P. Bishop, [https://www.microsoft.com/en-us/research/uploads/prod/2006/01/Bishop-Pattern-Recognition-and-Machine-Learning-2006.pdf Chapter 1].  
 
<!--
 
<!--
 
Refresh in your memory the gradient-based optimization, see either:
 
Refresh in your memory the gradient-based optimization, see either:

Revision as of 00:55, 5 October 2024

We are moving towards the coursework. How do you put your project description in one pitch? We reformulate the deliveries from Step 1 and Step 2 in an informal problem statement.

The seminar

  1. The warm-up 5-minute test
  2. Singular values decomposition and tensor product with demo
  3. The second slide and the third slide
  4. Homework discussion

Resources

Step 3 YouTube video

Homework

  1. For your selected project write the motivational part using this template for Step 3.
  2. Download the link to your homework here.
  3. Also, Step 2 homework reminder
  4. Refresh in your memory the Bayesian Statistics, see either:
    1. Covariance Matrix, Multivariate Normal Distribution, Generalized Linear Model, Ridge Regression, Bayesian inference
    2. the book by C.P. Bishop, Chapter 1.


Transcript of the video

Appears after the seminar.