Eyal Gomel (WD) speaks about decision trees here - https://www.youtube.com/watch?v=OGdWvp3YcIs&list=PLC7m9qp0Q1Ye3Fwnooz2k5xh0p5eD1s4k&index=26 

Recording of the meeting on validation 

https://www.youtube.com/watch?v=R--puYeB12c&list=PLC7m9qp0Q1Ye3Fwnooz2k5xh0p5eD1s4k&index=25&t=0s

Interesting annotated resource on ML compiled by Nahum  https://docs.google.com/document/d/1-y0vGpy4_2khxTzfWWNY9m4AN4tILjyrsc0jAFV8d2g/edit?usp=sharing

Using PCA to visualize your data by Guy Barash:   

Last meeting recording is available here:
https://urldefense.proofpoint.com/v2/url?u=https-3A__www.youtube.com_watch-3Fv-3D1PrwZszJtU0-26list-3DPLC7m9qp0Q1Ye3Fwnooz2k5xh0p5eD1s4k-26index-3D24&d=DwIGaQ&c=jf_iaSHvJObTbx-siA1ZOg&r=y_b69HJLyjn8lFwzYVfyxol578OEO4exeFDpgGN6MoQ&m=IQbifIhxvi7Pyt9E-dhZY1JNQL__Zdd4JOmaz806qA0&s=ZQkb4sKcfQ5ULUt__6que7PkAdXlsCvk-Gr6n1VSbyo&e=

The code is available here in Git:
https://urldefense.proofpoint.com/v2/url?u=https-3A__github.com_GuysBarash_PCA_blob_master_PCA.ipynb&d=DwIGaQ&c=jf_iaSHvJObTbx-siA1ZOg&r=y_b69HJLyjn8lFwzYVfyxol578OEO4exeFDpgGN6MoQ&m=IQbifIhxvi7Pyt9E-dhZY1JNQL__Zdd4JOmaz806qA0&s=W9AnTx1zx5zCwGabfD1Pzh5i_OeI5f8czg23cpMyBn4&e=

In colab:

https://urldefense.proofpoint.com/v2/url?u=https-3A__colab.research.google.com_github_GuysBarash_PCA_blob_master_PCA.ipynb&d=DwIGaQ&c=jf_iaSHvJObTbx-siA1ZOg&r=y_b69HJLyjn8lFwzYVfyxol578OEO4exeFDpgGN6MoQ&m=IQbifIhxvi7Pyt9E-dhZY1JNQL__Zdd4JOmaz806qA0&s=3tkEyYM9XKuH66WrESLMCKxIR_Ib5qC1CKWV7faklnI&e=

And the medium post:
https://urldefense.proofpoint.com/v2/url?u=https-3A__medium.com_-40guysbarash_using-2Dpca-2Dto-2Dvisualize-2Dyour-2Ddata-2D7c71f6f68a1b&d=DwIGaQ&c=jf_iaSHvJObTbx-siA1ZOg&r=y_b69HJLyjn8lFwzYVfyxol578OEO4exeFDpgGN6MoQ&m=IQbifIhxvi7Pyt9E-dhZY1JNQL__Zdd4JOmaz806qA0&s=nmGpKZAlQbwL7euqWWovgHcugfwRy0k0Aa7EWosjOTI&e=

We will revisit the concept of validation and explain model selection.   Both can be viewed as a special case of learning.   https://drive.google.com/file/d/1PI204IVAqDAgJDZYbow24FjuwWbj3rHg/view?usp=sharing

ML study group "official" site has been updated - https://www.research.ibm.com/haifa/dept/vst/ML-studygroup.shtml.    Enjoy.   

Samuel Ackerman JSM presentation on drift detection (was also given in the ML weekly meeting) -  https://ww2.amstat.org/meetings/jsm/2020/onlineprogram/ActivityDetails.cfm?SessionID=219879 

Guy Barash (WD) will speak on using PCA to analyze your model - https://medium.com/@guysbarash/using-pca-to-visualize-your-data-7c71f6f68a1b