Processor scheduling algorithms
Random boosting is a strategy used by the scheduler in Microsoft Windows to avoid deadlock due to priority inversion. Ready threads holding locks are randomly boosted in priority and allowed to run long enough to exit the critical section. If the thread doesn't get enough time to release the lock, it will get another chance. (Wikipedia).
Ensembles (3): Gradient Boosting
Gradient boosting ensemble technique for regression
From playlist cs273a
Gradient Boost Part 1 (of 4): Regression Main Ideas
Gradient Boost is one of the most popular Machine Learning algorithms in use. And get this, it's not that complicated! This video is the first part in a series that walks through it one step at a time. This video focuses on the main ideas behind using Gradient Boost to predict a continuous
From playlist StatQuest
Randomness Quiz - Applied Cryptography
This video is part of an online course, Applied Cryptography. Check out the course here: https://www.udacity.com/course/cs387.
From playlist Applied Cryptography
Pseudo Random Number Generator Solution - Applied Cryptography
This video is part of an online course, Applied Cryptography. Check out the course here: https://www.udacity.com/course/cs387.
From playlist Applied Cryptography
Gradient Boosting : Data Science's Silver Bullet
A dive into the all-powerful gradient boosting method! My Patreon : https://www.patreon.com/user?u=49277905
From playlist Data Science Concepts
Gradient Boost Part 2 (of 4): Regression Details
Gradient Boost is one of the most popular Machine Learning algorithms in use. And get this, it's not that complicated! This video is the second part in a series that walks through it one step at a time. This video focuses on the original Gradient Boost algorithm used to predict a continuou
From playlist StatQuest
Pseudo Random Number Generator - Applied Cryptography
This video is part of an online course, Applied Cryptography. Check out the course here: https://www.udacity.com/course/cs387.
From playlist Applied Cryptography
Quantization and Coding in A/D Conversion
http://AllSignalProcessing.com for more great signal-processing content: ad-free videos, concept/screenshot files, quizzes, MATLAB and data files. Real sampling systems use a limited number of bits to represent the samples of the signal, resulting in quantization of the signal amplitude t
From playlist Sampling and Reconstruction of Signals
Applied Machine Learning 2019 - Lecture 09 - Gradient boosting; Calibration
Gradient boosting and "extreme" gradient boosting Calibration curves and calibrating classifiers with CalibratedClassifierCV. Class website with slides and more materials: https://www.cs.columbia.edu/~amueller/comsw4995s19/schedule/
From playlist Applied Machine Learning - Spring 2019
Statistical Learning: 8.R.2 Random Forests and Boosting
Statistical Learning, featuring Deep Learning, Survival Analysis and Multiple Testing You are able to take Statistical Learning as an online course on EdX, and you are able to choose a verified path and get a certificate for its completion: https://www.edx.org/course/statistical-learning
From playlist Statistical Learning
Statistical Learning: 8.5 Boosting
Statistical Learning, featuring Deep Learning, Survival Analysis and Multiple Testing You are able to take Statistical Learning as an online course on EdX, and you are able to choose a verified path and get a certificate for its completion: https://www.edx.org/course/statistical-learning
From playlist Statistical Learning
Finding the Tallest Tree: comparing tree-based models
Tree-based models such as decision trees, random forests, and boosted trees provide powerful predictions and are fast to compute. There are many different ways to fit these models in R, including the rpart, randomForest, and xgboost packages. During this talk, we'll examine numerous ways t
From playlist Introduction to Machine Learning
Boosted and Differentially Private Ensembles of Decision Trees
A Google TechTalk, 2020/7/29, presented by Richard Nock, Data61 and The Australian National University ABSTRACT: Ensembles of decision tree (DT) classifiers are hugely popular in both the private and non-private settings, and display a very singular picture: while boosting and offsprings t
From playlist 2020 Google Workshop on Federated Learning and Analytics
Applied ML 2020 - 08 - Gradient Boosting
Materials at https://www.cs.columbia.edu/~amueller/comsw4995s20/schedule/
From playlist Applied Machine Learning 2020
Ensemble Learning | Ensemble Learning In Machine Learning | Machine Learning Tutorial | Simplilearn
🔥Artificial Intelligence Engineer Program (Discount Coupon: YTBE15): https://www.simplilearn.com/masters-in-artificial-intelligence?utm_campaign=EnsembleLearning&utm_medium=Descriptionff&utm_source=youtube 🔥Professional Certificate Program In AI And Machine Learning: https://www.simplilear
This lesson introduces the different sample methods when conducting a poll or survey. Site: http://mathispower4u.com
From playlist Introduction to Statistics
Ensemble techniques leverage many weak learners to create a strong learner! This video describes the basic principle, variance/bias tradeoff, homogeneous/heterogenous ensembles, bagging vs boosting vs stacking and some detailed walkthroughs of decision trees, random forests, adaboost, grad
From playlist Materials Informatics