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Morten Hjorth-Jensen
2021-11-04 17:06:24 +01:00
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README.md
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@@ -375,6 +375,7 @@ Recommended prereading: Chapters 1-2 (linear algebra) and chapter 3 (statistics)
### Week 44 November 1-5
- Lab Wednesday: Work on project 2
- Lecture Thursday: Summary on PCA and discussion of Clustering for unsupervised learning. Decision trees, classification and regression
- Video of Lecture at https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureNovember4.mp4?vrtx=view-as-webpage
- Lecture Friday: Decision trees, basic algorithms
- Reading recommendations:
- See lecture notes for week 44 at https://compphysics.github.io/MachineLearning/doc/web/course.html.
doc/LectureNotes/schedule.md
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@@ -135,23 +135,23 @@ For the reading assignments we use the following abbreviations:
- Lab Wednesday: Work on project 2
- Lecture Thursday: Recurrent Neural Networks
- Video of Lecture at https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureOctober28.mp4?vrtx=view-as-webpage
- Lecture Friday: Recurrent Neural Networks and principal component analysis (PCA)
- Video at https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureOctober29.mp4?vrtx=view-as-webpage
- Lecture Friday: Recurrent Neural Networks and time series and principal component analysis (PCA)
- Video of Lecture at https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureOctober29.mp4?vrtx=view-as-webpage
- Reading recommendations:
- See lecture notes for week 43 at https://compphysics.github.io/MachineLearning/doc/web/course.html.
- For RNNs, see Goodfellow et al chapter 10 and discussions in chapter 11 and 12 on practicalities and applications
- For PCA see lecture notes (jupyter book) chapter 11 and also chapter 12 on clustering. Geron's chapter 8 is also a good read.
- For PCA, see lecture notes chapter 11 and Geron's text chapter 8
### Week 44 November 1-5
- Lab Wednesday: Work on project 2
- Lecture Thursday: Decision trees, classification and regression
- Lecture Thursday: Summary on PCA and discussion of Clustering for unsupervised learning. Decision trees, classification and regression
- Video of Lecture at https://www.uio.no/studier/emner/matnat/fys/FYS-STK3155/h21/forelesningsvideoer/LectureNovember4.mp4?vrtx=view-as-webpage
- Lecture Friday: Decision trees, basic algorithms
- Reading recommendations:
- See lecture notes for week 44 at https://compphysics.github.io/MachineLearning/doc/web/course.html.
- Hastie et al sections 9.1 and 9.2
- Hastie et al sections 9.1 and 9.2. Geron's text chapter 6 (Decision trees) and chapter 8 on PCA and Clustering
### Week 45 November 8-12
- Lab Wednesday: Work on project 2 and start project 3
- Lab Wednesday: Work on project 2, project 3 available. Deadline project 2 is November 15.
- Lecture Thursday: Ensemble methods, bagging and random forests
- Lecture Friday: Boosting and gradient boosting
- Reading recommendations:
@@ -182,3 +182,4 @@ For the reading assignments we use the following abbreviations: