Introduction to Deep Learning by Andrew NG [COMPLETE]

Andrew Ng's course on deep learning and neural networks.

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State Space Representation of Differential Equations

In this video we show how to represent differential equations (either linear or non-linear) in state space form. This is useful as it allows us to combine an...

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Gaussian/Normal Distributions

In this video we discuss the Gaussian (AKA Normal) probability distribution function. We show how it relates to the error function (erf) and discuss how to ...

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Control Bootcamp: Sensitivity and Robustness

Here we show that peaks in the sensitivity function result in a lack of robustness.

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Peter Ponders PID - Simulation Methods, Which is Best?

This video compares 3 methods for doing simulations. Laplace transforms, state space and differential equations are compared examining their different adv... See More

Introduction to Bode Plots

In this video we introduce the concept of Bode plots including what they represent, how they are generated, as well as how to use Matlab tools to work with B...

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The Navigation Equations: Computing Position North, East, and Down

In this video we show how to compute the inertial velocity of a rigid body in the vehicle-carried North, East, Down (NED) frame. This is achieved by rotating the velocity expressed in the...

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Peter Ponders PID - System Identification Basics

Transfer functions don't come with the machine you are trying to control. Transfer functions must be estimated using system identification techniques. With... See More

Parseval's Theorem

Parseval's theorem is an important result in Fourier analysis that can be used to put guarantees on the accuracy of signal approximation in the Fourier domain.

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Lecture 25: Nyquist stability criterion

Discusses some basic concepts, Principle of Argument and hence, Nyquist stability criterion See More

Derivation of Rodrigues’ Rotation Formula

In this video we explain and derive Rodrigues’ Rotation Formula. This functions describes how to rotate an arbitrary vector about another arbitrary axis of rotation. This has applications to...

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Lecture 9: Time response and Time domain specifications

In this lecture, Time response is discussed in detail. Also discussed are different time domain specifications See More

Time domain - tutorial 7: system properties

In this video, we cover system properties. The concept of memoryless, causal, stable, invertible, time-invariant and linear systems is intuitively explained...

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Frequency domain – tutorial 6: Fourier transform tables

In this video, we learn about Fourier transform tables which enable us to quickly travel from time to the frequency domain. The main learning objective is to...

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Singular Value Decomposition (SVD): Matrix Approximation

This video describes how the singular value decomposition (SVD) can be used for matrix approximation.

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Course Introduction (Signal Processing 101)

Learn Signal Processing 101 in 31 lectures covering time, frequency and Laplace domain in about 8 hours all together:https://www.youtube.com/watch?v=KZd68xga...

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Linear Systems [Control Bootcamp]

Linear systems of ordinary differential equations are analyzed using eigenvalues and eigenvectors. This will be the mathematical foundation of this bootcamp on linear control theory.

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Feedback Control and Block Diagram Introduction

How do engineers begin to design controllers to respond to disturbances and maintain set points? In this example, I'll discuss how we can design a controller...

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Stanford CS234: Reinforcement Learning | Winter 2019 | Lecture 13 - Fast Rei...

Professor Emma Brunskill
Assistant Professor, Computer Science
Stanford AI for Human Impact Lab
Stanford Artificial Intelligence Lab
Statistical Machine Learning Group

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Types of Machine Learning 1

This lecture gives an overview of the main categories of machine learning, including supervised, un-supervised, and semi-supervised techniques, depending on the availability of expert labels...

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Internal Model Control IMC Introduction

Internal Model Control IMC Introduction

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RL Course by David Silver - Lecture 9: Exploration and Exploitation

An overview of multi-armed bandits, contextual bandits and Markov Decision Processes.

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Control Systems in Practice, Part 6: What Are Non-Minimum Phase Systems?

We like to categorize transfer functions into groups and label them because it helps us understand how a particular system will behave simply by knowing the group that it’s part of. We gain...

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First Order Dynamics in Process Control

An overview on the identification and behavior of first order dynamics in process control.

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Controllability [Control Bootcamp]

This lecture explores when a linear system is controllable. We begin with the simple test in terms of the rank of the controllability matrix on a few intuitive examples.

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