Difference between revisions of "Step 3"
From Research management course
| (2 intermediate revisions by the same user not shown) | |||
| 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, | + | ## 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: | ||
| Line 24: | Line 23: | ||
--> | --> | ||
<!--statistical and Bayesian inference--> | <!--statistical and Bayesian inference--> | ||
| + | |||
| + | === Schemes for the second slide === | ||
| + | ====Scheme 1==== | ||
| + | # Problem to research | ||
| + | # Method | ||
| + | # Contribution | ||
| + | ====Scheme 2==== | ||
| + | # Problem to solve | ||
| + | # Problem statement | ||
| + | # Soluton | ||
| + | ====Scheme 3==== | ||
| + | # Goal | ||
| + | # Alternatives | ||
| + | # Choise reasoning | ||
<!--==Fun==--> | <!--==Fun==--> | ||
Latest revision as of 01:01, 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.
Contents
The seminar
- The warm-up 5-minute test
- Singular values decomposition and tensor product with demo
- The second slide and the third slide
- Homework discussion
Resources
Step 3 YouTube video
Homework
- For your selected project write the motivational part using this template for Step 3.
- Download the link to your homework here.
- Also, Step 2 homework reminder
- Refresh in your memory the Bayesian Statistics, see either:
- Covariance Matrix, Multivariate Normal Distribution, Generalized Linear Model, Ridge Regression, Bayesian inference
- the book by C.P. Bishop, Chapter 1.
Schemes for the second slide
Scheme 1
- Problem to research
- Method
- Contribution
Scheme 2
- Problem to solve
- Problem statement
- Soluton
Scheme 3
- Goal
- Alternatives
- Choise reasoning
Transcript of the video
Appears after the seminar.