Courses_ML_DL3

https://explained.ai/gradient-boosting/ https://amueller.github.io/aml/index.html https://harvard-iacs.github.io/2017-CS109A/labs/lab9/notebook/ https://harvard-iacs.github.io/2018-CS109A/labs/lab-9/solutions/ https://harvard-iacs.github.io/2020-CS109A/lectures/lecture25/notebook/ https://stackoverflow.com/questions/57116146/why-whenever-i-refresh-my-random-forest-regressor-the-mse-and-mae-change-why-d?rq=1 https://stats.stackexchange.com/questions/354336/what-happens-when-bootstrapping-isnt-used-in-sklearn-randomforestclassifier https://datascience.stackexchange.com/questions/43542/mean-absolute-error-in-random-forest-regression https://towardsdatascience.com/prettifying-partial-density-plots-in-python-1f7216937ff https://www.kaggle.com/dansbecker/learn-machine-learning https://stats.stackexchange.com/questions/234177/how-to-detect-nonlinear-relationship https://stats.stackexchange.com/questions/218127/intuition-behind-pearson-correlation-co-variance-and-cosine-similarity https://arxiv.org/pdf/1610.09659.pdf https://projecteuclid.org/journals/statistical-science/volume-16/issue-3/Statistical-Modeling--The-Two-Cultures-with-comments-and-a/10.1214/ss/1009213726.full https://stackoverflow.com/questions/15810339/how-are-feature-importances-in-randomforestclassifier-determined https://www.stat.berkeley.edu/~breiman/RandomForests/cc_home.htm#varimp https://link.springer.com/article/10.1186/1471-2105-8-25 https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-9-307

numeristical

https://www.youtube.com/c/numeristical/videos

Sanjoy Das

https://www.youtube.com/user/orissabbsr/playlists

ADAMS Tutorial

https://www.youtube.com/playlist?list=PLouxP1LEXV4mEdMWOOPXvZ3toE22JL1tf

Foundation for Armenian Science and Technology (FAST)

https://www.youtube.com/channel/UCFxztZtvgd1lIp1YYeTMEOQ/playlists

AMILE - Machine Learning with Christian Nabert

https://www.youtube.com/channel/UCgQlZ6kefvYeHDe__YkFluA/playlists

https://ml-course.github.io/master/ https://www.youtube.com/c/MachineLearningforEngineers/videos

CS-E4710 - Machine Learning: Supervised Methods D, 08.09.2020-18.12.2020

https://mycourses.aalto.fi/course/view.php?id=28204&section=3 https://mycourses.aalto.fi/course/index.php?categoryid=35 https://www.youtube.com/user/alexjung111/playlists https://www.youtube.com/playlist?list=PLrbn2dGrLJK9k0ekFun1vxE7CT--2VfJJ

CS-EJ3211 - Machine Learning with Python D, 29.03.2021-04.06.2021

https://mycourses.aalto.fi/course/view.php?id=30781

https://people.eecs.berkeley.edu/~demmel/ma221_Spr20/ https://arxiv.org/pdf/2006.04750.pdf Nonparametric Feature Impact and Importance

https://botlnec.github.io/islp/

Data Science Conference

https://www.youtube.com/channel/UC-yt9rh6xh9Ym0vtTIA105w/playlists

Introduction to Statistical Ideas and Methods

https://www.youtube.com/channel/UC0O0KvBZk341KXsSFAYr_1g/videos

https://escape2020.github.io/school2021/ https://www.youtube.com/playlist?list=PL5l3baTu76qPbYZlRK0Yhr4P_wsI-84Hn

https://uvadlc.github.io/ https://www.youtube.com/channel/UCpvn0ycxIA6Uf8W00OX3frQ/playlists https://uvadlc-notebooks.readthedocs.io/en/latest/index.html

https://twitter.com/PiyalBanik/status/1416612450376454144 https://twitter.com/YairZick/status/1416238133893533697 http://www.stat.columbia.edu/~gelman/ https://avehtari.github.io/ROS-Examples/ http://www.stat.columbia.edu/~gelman/arm/

civilengineeringprof

https://www.youtube.com/user/civilengineeringprof/playlists

Samuel S. Watson

https://www.youtube.com/user/samuelswatson/playlists

Kaggle

https://www.kaggle.com/abhinand05/catboost-a-deeper-dive https://www.kaggle.com/subbhashit/car-price-approaching-any-regression-problem-99?scriptVersionId=48279382 https://www.kaggle.com/akashram/intro-to-boosting-models-categorical-data-nlp https://github.com/cpmech/gosl

https://atcold.github.io/pytorch-Deep-Learning/ https://www.bradyneal.com/causal-inference-course https://dev.mrdbourke.com/tensorflow-deep-learning/ https://github.com/ahmedbahaaeldin/From-0-to-Research-Scientist-resources-guide https://ki-campus.org/index.php/courses/automl-luh2021?locale=en https://sebastianraschka.com/blog/2021/dl-course.html https://tvm.d2l.ai/chapter_gpu_schedules/index.html https://valdanchev.github.io/reproducible-data-science-python/intro.html http://www.doc.mmu.ac.uk/STAFF/S.Lynch/Python_for_A_Level_Mathematics_and_Beyond.html https://m.youtube.com/playlist?list=PLUgbVHjDharjx-JM53l37cAxx1NIlCz9- https://m.youtube.com/channel/UC7m0STJK9e4BbD-elwS4bNw/videos https://random-matrix-learning.github.io/#presentation1 https://uni-tuebingen.de/de/203146 http://www.matthewpratola.com/teaching/stat8810-fall-2017/

MATH 122 Applied calculus Thomas Hamori

https://www.youtube.com/channel/UCO9ePGcp8KV52tP0j5rgxkQ/playlists

Machine Learning for Healthcare

https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-s897-machine-learning-for-healthcare-spring-2019/ https://www.youtube.com/playlist?list=PLUl4u3cNGP60B0PQXVQyGNdCyCTDU1Q5j

LxMLS Lisbon Machine Learning School

https://www.youtube.com/c/LxMLSLisbonMachineLearningSchool/playlists

Half Sleeves

https://www.youtube.com/channel/UCVBtWPeW8CMbf5y5JjHv_Yg/videos

cscsch

https://www.youtube.com/user/cscsch/playlists

Harvard Applied Math 205

https://courses.seas.harvard.edu/courses/am205/ https://www.youtube.com/channel/UC3KiLqlUjliL37fA-j4ctmQ/playlists

Kaggle (practise Feature Engineering and learn from older comps/solutions.)

https://www.kaggle.com/c/grupo-bimbo-inventory-demand https://www.kaggle.com/c/bnp-paribas-cardif-claims-management/overview https://www.kaggle.com/c/walmart-recruiting-store-sales-forecasting https://www.kaggle.com/c/avazu-ctr-prediction https://www.kaggle.com/c/walmart-recruiting-trip-type-classification https://www.kaggle.com/c/homesite-quote-conversion https://www.kaggle.com/c/rossmann-store-sales https://www.kaggle.com/c/telstra-recruiting-network https://www.kaggle.com/mdfahimreshm/bert-in-depth-understanding aaannd... of course, all the Santander ones.

https://seaborn.pydata.org/generated/seaborn.regplot.html

List of CVPR 2021 Tutorials and Workshop Language for 3D Scenes https://lnkd.in/gAbs6ck

Frontiers of Monocular 3D Perception https://lnkd.in/guTKDB9

Beyond Fairness: Towards a Just, Equitable, and Accountable Computer Vision https://lnkd.in/gGVe8mq

Responsible Computer Vision https://lnkd.in/gURCCHg

Affective Understanding in Video https://lnkd.in/gyjEHKN

When Image Analysis Meets Natural Language Processing: A Case Study in Radiology https://lnkd.in/gVfYFKg

New Frontiers in Data-Driven Autonomous Driving https://lnkd.in/gAaK4Qy

International Challenge on Activity Recognition (ActivityNet) https://lnkd.in/g2EFB_T

Medical Computer Vision https://lnkd.in/giUSYP7

International Workshop on Dynamic Scene Reconstruction https://lnkd.in/gFRSQGm

Workshop on Event-based Vision https://lnkd.in/gdnNDYs

New Frontiers in Data-Driven Autonomous Driving https://lnkd.in/gAaK4Qy

Cross-View and Cross-Modal Visual Geo-Localization https://lnkd.in/gA-5Bc4

Data- and Label-Efficient Learning in An Imperfect World https://lnkd.in/g8x8fhh

From VQA to VLN: Recent Advances in Vision-and-Language Research https://lnkd.in/g4_cbpJ

Autonomous Driving: Perception, Prediction and Planning https://lnkd.in/gGA8N2j

Theory and Application of Energy-Based Generative Models https://lnkd.in/g6K72WU

Adversarial Machine Learning in Computer Vision https://lnkd.in/ggpxCTE

Leave Those Nets Alone: Advances in Self-Supervised Learning: IEEE CVPR 2021 Tutorial https://lnkd.in/gmRZAzR

Autonomous Driving: IEEE CVPR 2021 Tutorial https://lnkd.in/gsdNWPZ

Normalization Techniques in Deep Learning: Methods, Analyses, and Applications: IEEE CVPR 2021 Tutorial https://lnkd.in/gxZzBYB

Fine-Grained Visual Categorization: IEEE CVPR 2021 Tutorial https://lnkd.in/gKvSnjy

Binary Networks for Computer Vision: IEEE CVPR 2021 Workshop https://lnkd.in/gWD3CXN

Some Recent Data Science, Deep Learning and Computer Vision Courses | 2021 Deep Learning for Computer Vision (DL4CV) by WIAC, Spring 2021 https://lnkd.in/g4_fscc DS-GA 1013/Math-GA 2824: Mathematical Tools for Data Science - Lectures | 2021 https://lnkd.in/gazA9z2 Latest Links Responsible Computer Vision : IEEE CVPR 2021 Workshop https://lnkd.in/gURCCHg Affective Understanding in Video: IEEE CVPR 2021 Workshop https://lnkd.in/gyjEHKN When Image Analysis Meets Natural Language Processing: A Case Study in Radiology: IEEE CVPR 2021 Tutorial https://lnkd.in/gVfYFKg New Frontiers in Data-Driven Autonomous Driving: IEEE CVPR 2021 Tutorial https://lnkd.in/gAaK4Qy International Challenge on Activity Recognition (ActivityNet): IEEE CVPR 2021 Workshop https://lnkd.in/g2EFB_T Medical Computer Vision: IEEE CVPR 2021 Workshop https://lnkd.in/giUSYP7 International Workshop on Dynamic Scene Reconstruction: IEEE CVPR 2021 Workshop https://lnkd.in/gFRSQGm Workshop on Event-based Vision: IEEE CVPR 2021 Workshop https://lnkd.in/gdnNDYs New Frontiers in Data-Driven Autonomous Driving: IEEE CVPR 2021 Tutorial https://lnkd.in/gAaK4Qy Cross-View and Cross-Modal Visual Geo-Localization: IEEE CVPR 2021 Tutorial https://lnkd.in/gA-5Bc4