Estimation theory | Parametric statistics | Regression variable selection | Single-equation methods (econometrics)
In statistics, least-angle regression (LARS) is an algorithm for fitting linear regression models to high-dimensional data, developed by Bradley Efron, Trevor Hastie, Iain Johnstone and Robert Tibshirani. Suppose we expect a response variable to be determined by a linear combination of a subset of potential covariates. Then the LARS algorithm provides a means of producing an estimate of which variables to include, as well as their coefficients. Instead of giving a vector result, the LARS solution consists of a curve denoting the solution for each value of the L1 norm of the parameter vector. The algorithm is similar to forward stepwise regression, but instead of including variables at each step, the estimated parameters are increased in a direction equiangular to each one's correlations with the residual. (Wikipedia).
CCSS What is the difference between Acute, Obtuse, Right and Straight Angles
π Learn how to define angle relationships. Knowledge of the relationships between angles can help in determining the value of a given angle. The various angle relationships include: vertical angles, adjacent angles, complementary angles, supplementary angles, linear pairs, etc. Vertical a
From playlist Angle Relationships
What are acute, obtuse, right, and straight angles
π Learn how to define angle relationships. Knowledge of the relationships between angles can help in determining the value of a given angle. The various angle relationships include: vertical angles, adjacent angles, complementary angles, supplementary angles, linear pairs, etc. Vertical a
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What is an angle and it's parts
π Learn how to define angle relationships. Knowledge of the relationships between angles can help in determining the value of a given angle. The various angle relationships include: vertical angles, adjacent angles, complementary angles, supplementary angles, linear pairs, etc. Vertical a
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Angle Side Relationships in a Triangle - Geometry
This video focuses on the angle side relationships in a triangle. In particular, I show students how to use the idea that the smallest angle is opposite the smallest side. This concept is used to order the sides of the triangle from least to greatest. Your feedback and requests are encour
From playlist Geometry
Determining if two angles are adjacent or not
π Learn how to define and classify different angles based on their characteristics and relationships are given a diagram. The different types of angles that we will discuss will be acute, obtuse, right, adjacent, vertical, supplementary, complementary, and linear pair. The relationships
From playlist Angle Relationships From a Figure
Label the angle in three different ways
π Learn how to define angle relationships. Knowledge of the relationships between angles can help in determining the value of a given angle. The various angle relationships include: vertical angles, adjacent angles, complementary angles, supplementary angles, linear pairs, etc. Vertical a
From playlist Angle Relationships
What are adjacent angles and linear pairs
π Learn how to define angle relationships. Knowledge of the relationships between angles can help in determining the value of a given angle. The various angle relationships include: vertical angles, adjacent angles, complementary angles, supplementary angles, linear pairs, etc. Vertical a
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Computational Linear Algebra 8: Numba, Polynomial Features, How to Implement Linear Regression
Predicting health outcomes on a diabetes data set with least squares linear regression: - Linear regression in sklearn - Polynomial Features - Speeding up with Numba - Regularization and Noise How to implement linear regression yourself: - How did Scikit Learn do it? - Naive solution - No
From playlist Computational Linear Algebra
Tommi Jaakola - Diffusion based distributional modeling of conformers, blind docking and proteins
Recorded 24 January 2023. Tommi Jaakkola of the Massachusetts Institute of Technology presents "Diffusion based distributional modeling of conformers, blind docking and proteins" at IPAM's Learning and Emergence in Molecular Systems Workshop. Learn more online at: http://www.ipam.ucla.edu/
From playlist 2023 Learning and Emergence in Molecular Systems
Ming Yuan: "Low Rank Tensor Methods in High Dimensional Data Analysis (Part 2/2)"
Watch part 1/2 here: https://youtu.be/K8t24xm7tn8 Tensor Methods and Emerging Applications to the Physical and Data Sciences Tutorials 2021 "Low Rank Tensor Methods in High Dimensional Data Analysis (Part 2/2)" Ming Yuan - Columbia University, Statistics Abstract: Large amount of multid
From playlist Tensor Methods and Emerging Applications to the Physical and Data Sciences 2021
Every Distance in Data Science (Almost 100K Subs!)
0:00 Intro 2:19 Euclidean Distance 5:47 Manhattan Distance 9:14 Minkowski Distance 12:49 Chebyshev Distance 15:40 Cosine Distance 19:35 Hamming Distance 20:17 Haversine Distance Lasso Regression : https://www.youtube.com/watch?v=jbwSCwoT51M Curse of Dimensionality : https://www.youtube.c
From playlist Data Science Basics
Learn how to classify your four major angles
π Learn how to define angle relationships. Knowledge of the relationships between angles can help in determining the value of a given angle. The various angle relationships include: vertical angles, adjacent angles, complementary angles, supplementary angles, linear pairs, etc. Vertical a
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Andrew Ferguson: "Machine learning-enabled enhanced sampling in biomolecular simulation and..."
Machine Learning for Physics and the Physics of Learning Tutorials 2019 "Machine learning-enabled enhanced sampling in biomolecular simulation and data-driven design of self-assembling photonic crystals and optoelectonic Ο-conjugated oligopeptides" Andrew Ferguson, University of Chicago -
From playlist Machine Learning for Physics and the Physics of Learning 2019
Parametrizations of circle, ellipse, and cycloid -- Calculus II
This lecture is on Calculus II. It follows Part II of the book Calculus Illustrated by Peter Saveliev. The text of the book can be found at http://calculus123.com.
From playlist Calculus II
MIT 18.650 Statistics for Applications, Fall 2016 View the complete course: http://ocw.mit.edu/18-650F16 Instructor: Philippe Rigollet In this lecture, Prof. Rigollet talked about linear regression and multivariate case. License: Creative Commons BY-NC-SA More information at http://ocw.m
From playlist MIT 18.650 Statistics for Applications, Fall 2016
Professor StΓ©phane Mallat: "High-Dimensional Learning and Deep Neural Networks"
The Turing Lectures: Mathematics - Professor StΓ©phane Mallat: High-Dimensional Learning and Deep Neural Networks Click the below timestamps to navigate the video. 00:00:07 Welcome by Professor Andrew Blake, Director, The Alan Turing Institute 00:01:36 Introduction by Professo
From playlist Turing Lectures
π Learn how to define angle relationships. Knowledge of the relationships between angles can help in determining the value of a given angle. The various angle relationships include: vertical angles, adjacent angles, complementary angles, supplementary angles, linear pairs, etc. Vertical a
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Lecture 17 | Machine Learning (Stanford)
Lecture by Professor Andrew Ng for Machine Learning (CS 229) in the Stanford Computer Science department. Professor Ng discusses the topic of reinforcement learning, focusing particularly on continuous state MDPs, discretization, and policy and value iterations. This course provides a
From playlist Lecture Collection | Machine Learning
π Learn how to define angle relationships. Knowledge of the relationships between angles can help in determining the value of a given angle. The various angle relationships include: vertical angles, adjacent angles, complementary angles, supplementary angles, linear pairs, etc. Vertical a
From playlist Angle Relationships