Mathematical optimization | First order methods | Gradient methods | Optimization algorithms and methods
In mathematics, gradient descent (also often called steepest descent) is a first-order iterative optimization algorithm for finding a local minimum of a differentiable function. The idea is to take repeated steps in the opposite direction of the gradient (or approximate gradient) of the function at the current point, because this is the direction of steepest descent. Conversely, stepping in the direction of the gradient will lead to a local maximum of that function; the procedure is then known as gradient ascent. Gradient descent is generally attributed to Augustin-Louis Cauchy, who first suggested it in 1847. Jacques Hadamard independently proposed a similar method in 1907. Its convergence properties for non-linear optimization problems were first studied by Haskell Curry in 1944, with the method becoming increasingly well-studied and used in the following decades. (Wikipedia).
This video follows on from the discussion on linear regression as a shallow learner ( https://www.youtube.com/watch?v=cnnCrijAVlc ) and the video on derivatives in deep learning ( https://www.youtube.com/watch?v=wiiPVB9tkBY ). This is a deeper dive into gradient descent and the use of th
From playlist Introduction to deep learning for everyone
Introduction to Gradient Descent
An introduction to gradient descent. See also https://youtu.be/W2pSn_t0KYs
From playlist gradient_descent
Gradient Descent : Data Science Concepts
A technique that comes up over and over again in all parts of data science! Link to Code : https://github.com/ritvikmath/YouTubeVideoCode/blob/main/Gradient%20Descent.ipynb My Patreon : https://www.patreon.com/user?u=49277905
From playlist Data Science Code
See also https://youtu.be/BYTi0RWp494 and https://youtu.be/vV_vIFL3LKU
From playlist gradient_descent
See also https://youtu.be/W2pSn_t0KYs and https://youtu.be/x7QYZ4n3A8M
From playlist gradient_descent
Powered by https://www.numerise.com/ Gradient of a line segment 1
From playlist Linear sequences & straight lines
What is Gradient, and Gradient Given Two Points
"Find the gradient of a line given two points."
From playlist Algebra: Straight Line Graphs
Gradient Descent, Step-by-Step
Gradient Descent is the workhorse behind most of Machine Learning. When you fit a machine learning method to a training dataset, you're probably using Gradient Descent. It can optimize parameters in a wide variety of settings. Since it's so fundamental to Machine Learning, I decided to mak
From playlist Optimizers in Machine Learning
Gradient Descent Machine Learning | Gradient Descent Algorithm | Stochastic Gradient Descent Edureka
๐ฅEdureka ๐๐ ๐๐ข๐ฉ๐ฅ๐จ๐ฆ๐ ๐ข๐ง ๐๐ & ๐๐๐๐ก๐ข๐ง๐ ๐๐๐๐ซ๐ง๐ข๐ง๐ from E & ICT Academy of ๐๐๐ ๐๐๐ซ๐๐ง๐ ๐๐ฅ (๐๐ฌ๐ ๐๐จ๐๐: ๐๐๐๐๐๐๐๐๐): https://www.edureka.co/executive-programs/machine-learning-and-ai This Edureka video on ' Gradient Descent Machine Learning' will give you an overview of Gradient Descent Algorithm and
From playlist Data Science Training Videos
Stochastic Gradient Descent: where optimization meets machine learning- Rachel Ward
2022 Program for Women and Mathematics: The Mathematics of Machine Learning Topic: Stochastic Gradient Descent: where optimization meets machine learning Speaker: Rachel Ward Affiliation: University of Texas, Austin Date: May 26, 2022 Stochastic Gradient Descent (SGD) is the de facto op
From playlist Mathematics
Deep Learning Lecture 4.3 - Stochastic Gradient Descent
Deep Learning Lecture: Optimization Methods - Stochastic Gradient Descent (SGD) - SGD with Momentum
From playlist Deep Learning Lecture
Stochastic Gradient Descent and Machine Learning (Lecture 4) by Praneeth Netrapalli
PROGRAM: BANGALORE SCHOOL ON STATISTICAL PHYSICS - XIII (HYBRID) ORGANIZERS: Abhishek Dhar (ICTS-TIFR, India) and Sanjib Sabhapandit (RRI, India) DATE & TIME: 11 July 2022 to 22 July 2022 VENUE: Madhava Lecture Hall and Online This school is the thirteenth in the series. The schoo
From playlist Bangalore School on Statistical Physics - XIII - 2022 (Live Streamed)
Stochastic Gradient Descent | Why and How it Works?
This video contains all the conceptual details of the stochastic gradient descent and mini-batch gradient descent with a python implementation! I know it's a longer video than usual but I guess you'll enjoy the learning. #machinelearning #stochasticgradientdescent #python For more videos
From playlist ML Algorithms from Scratch
How to Escape Saddle Points Efficiently by Praneeth Netrapalli
DISCUSSION MEETING : STATISTICAL PHYSICS OF MACHINE LEARNING ORGANIZERS : Chandan Dasgupta, Abhishek Dhar and Satya Majumdar DATE : 06 January 2020 to 10 January 2020 VENUE : Madhava Lecture Hall, ICTS Bangalore Machine learning techniques, especially โdeep learningโ using multilayer n
From playlist Statistical Physics of Machine Learning 2020
Mini Batch Gradient Descent | Deep Learning | with Stochastic Gradient Descent
Mini Batch Gradient Descent is an algorithm that helps to speed up learning while dealing with a large dataset. Instead of updating the weight parameters after assessing the entire dataset, Mini Batch Gradient Descent updates weight parameters after assessing the small batch of the datase
From playlist Optimizers in Machine Learning
Artificial Intelligence & Machine Learning 4 - Stochastic Gradient Descent | Stanford CS221 (2021)
For more information about Stanford's Artificial Intelligence professional and graduate programs visit: https://stanford.io/ai Associate Professor Percy Liang Associate Professor of Computer Science and Statistics (courtesy) https://profiles.stanford.edu/percy-liang Assistant Professor
From playlist Stanford CS221: Artificial Intelligence: Principles and Techniques | Autumn 2021
Lecture 0110 Gradient descent intuition
Machine Learning by Andrew Ng [Coursera] 01-02 Linear regression with one variable
From playlist Machine Learning by Professor Andrew Ng