Random Processes and Stationarity
http://AllSignalProcessing.com for more great signal-processing content: ad-free videos, concept/screenshot files, quizzes, MATLAB and data files. Introduction to describing random processes using first and second moments (mean and autocorrelation/autocovariance). Definition of a stationa
From playlist Random Signal Characterization
Discrete-Time Dynamical Systems
This video shows how discrete-time dynamical systems may be induced from continuous-time systems. https://www.eigensteve.com/
From playlist Data-Driven Dynamical Systems
(ML 19.2) Existence of Gaussian processes
Statement of the theorem on existence of Gaussian processes, and an explanation of what it is saying.
From playlist Machine Learning
This lesson introduces the topic of scheduling and define basic scheduling vocabulary. Site: http://mathispower4u.com
From playlist Scheduling
What is predictive maintenance on electric motors - low power motors
In this episode we look more closely at the predictive maintenance strategy, and how it allows maintenance resources to be deployed more efficiently, which in turn improves performance and extends the lifetime of the motor. By minimizing outages caused by failed motors, plant productivity
From playlist Predictive maintenance
Physics Simulations and Simulating the Human Brain
How physics simulations can predict future probabilities, and applying this to the human brain. My Patreon page is at https://www.patreon.com/EugeneK
From playlist Physics
(ML 7.7.A2) Expectation of a Dirichlet random variable
How to compute the expected value of a Dirichlet distributed random variable.
From playlist Machine Learning
Statistics: Introduction (10 of 13) Variability
Visit http://ilectureonline.com for more math and science lectures! We will discuss variability: The accuracy of statistical results depend on the (sources of) variability of the collected data. To donate: http://www.ilectureonline.com/donate https://www.patreon.com/user?u=3236071 . Next
From playlist STATISTICS CH 1 INTRODUCTION
From playlist COMP0168 (2020/21)
From playlist COMP0168 (2020/21)
Special Topics - The Kalman Filter (7 of 55) The Multi-Dimension Model 1
Visit http://ilectureonline.com for more math and science lectures! In this video I will explain the overview of the Kalman filter on a multi dimension model. Next video in this series can be seen at: https://youtu.be/F7vQXNro7pE
From playlist SPECIAL TOPICS 1 - THE KALMAN FILTER
Stanford CS229: Machine Learning | Summer 2019 | Lecture 9 - Bayesian Methods - Parametric & Non
For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/3ptRUmB Anand Avati Computer Science, PhD To follow along with the course schedule and syllabus, visit: http://cs229.stanford.edu/syllabus-summer2019.html
From playlist Stanford CS229: Machine Learning Course | Summer 2019 (Anand Avati)
Learn TensorFlow.js - Deep Learning and Neural Networks with JavaScript
This full course introduces the concept of client-side artificial neural networks. We will learn how to deploy and run models along with full deep learning applications in the browser! To implement this cool capability, we’ll be using TensorFlow.js (TFJS), TensorFlow’s JavaScript library.
From playlist Machine Learning
MA Model Code Example : Time Series Talk
Coding the MA Model: - Generate your own MA process - Use ACF and PACF to determine order of MA process - Build the model - Make predictions Code used in this video: https://github.com/ritvikmath/Time-Series-Analysis/blob/master/MA%20Model.ipynb
From playlist Time Series Analysis
Keras with TensorFlow Course - Python Deep Learning and Neural Networks for Beginners Tutorial
This course will teach you how to use Keras, a neural network API written in Python and integrated with TensorFlow. We will learn how to prepare and process data for artificial neural networks, build and train artificial neural networks from scratch, build and train convolutional neural ne
From playlist Machine Learning
Special Topics - The Kalman Filter (18 of 55) What is a Covariance Matrix?
Visit http://ilectureonline.com for more math and science lectures! In this video I will explain what is the state covariance matrix, process noise covariance matrix, and measurement covariance matrix. Next video in this series can be seen at: https://youtu.be/ieL0jxzLhCE
From playlist SPECIAL TOPICS 1 - THE KALMAN FILTER
Can You Validate These Emails?
Email Validation is a procedure that verifies if an email address is deliverable and valid. Can you validate these emails?
From playlist Fun
Slides and more information: https://mml-book.github.io/slopes-expectations.html
From playlist There and Back Again: A Tale of Slopes and Expectations (NeurIPS-2020 Tutorial)