17:06

Introduction to Machine Learning: NN Time-Stepper

28:53

Introduction to Machine Learning: Feed-Forward NN

16:44

Introduction to Machine Learning: Stochastic Gradient Descent

17:42

Introduction to Machine Learning: Backpropagation

19:20

Introduction to Machine Learning: Neural Network Architectures

26:00

Introduction to Machine Learning: Neural Networks

22:41

Introduction to Machine Learning: Support Vector Machines

15:37

Introduction to Machine Learning: Classification Trees

15:01

Introduction to Machine Learning: Supervised learning algorithms

30:48

Introduction to Machine Learning: Unsupervised learning algorithms

30:54

Introduction to Machine Learning: Supervised versus unsupervised learning

06:04

Scientific Computing: Time-Stepping Implementation

22:18

Scientific Computing: Time-Stepping Errors and Stability

25:48

Scientific Computing: Time-Stepping Schemes

23:07

Scientific Computing: Numerical Integration

14:15

Scientific Computing: Numerical Differentiation Error Analysis

26:39

Scientific Computing: Numerical Differentiation

19:47

Introduction to Python: Root Finding Algorithm

12:42

Introduction to Python: Logic FOR/IF

22:11

Introduction to Python: Matrices & Vectors

35:18

Common Task Framework for Science and Engineering

05:44

Portable Video Studio: ATEM software controls

03:40

Portable Video Studio: The results!

05:07

Portable Video Studio: Setting up studio

07:42

Portable Video Studio: Connection Guide

08:28

Portable Video Studio: Components and Parts

20:05

Introduction to Signal Processing: Analysis of Bode Plots (Lecture 28)

12:47

Introduction to Signal Processing: Bode Plots and Differential Equations (Lecture 27)

18:41

Introduction to Signal Processing: Filters and Properties (Lecture 26)

14:02

Introduction to Signal Processing: Time-Frequency Filtering (Lecture 25)

11:41

Introduction to Signal Processing: Difference Equations (Lecture 24)

08:38

Introduction to Signal Processing: Signal Convolutions and Multiplication (Lecture 23)

22:14

Introduction to Signal Processing: Discrete Time Fourier transform (Lecture 22)

16:40

Introduction to Signal Processing: Differential Equations and FFT (Lecture 21)

21:48

Introduction to Signal Processing: Convolutions and Signal Modulation (Lecture 20)

17:13

Introduction to Signal Processing: Properties of the Fourier transform (Lecture 19)

16:25

Introduction to Signal Processing: Properties of the Fourier transform (Lecture 18)

15:47

Introduction to Signal Processing: The Fourier Transform (Lecture 17)

20:05

Introduction to Signal Processing: Frequency Filters (Lecture 16)

17:05

Introduction to Signal Processing: Input-Output with Fourier Series (Lecture 15)

16:44

Introduction to Signal Processing: Fourier Series Expansion of Signal (Lecture 14)

20:55

Introduction to Signal Processing: Convergence of Fourier Series (Lecture 12)

13:38

Introduction to Signal Processing: Discrete Fourier Series (Lecture 13)

29:37

Introduction to Signal Processing: Fourier Series (Lecture 11)

23:20

Introduction to Signal Processing: Singular Functions (Lecture 10)

16:59

Introduction to Signal Processing: LTI Differential Equations (Lecture 9)

22:30

Introduction to Signal Processing: LTI System Properties (Lecture 8)

21:27

Introduction to Signal Processing: Continuous LTI Systems (Lecture 7)

18:22

Introduction to Signal Processing: LTI Systems (Lecture 6)

22:16

Introduction to Signal Processing: Properties of Signals (Lecture 5)

22:23

Introduction to Signal Processing: Impulses and Steps (Lecture 4)

31:03

Introduction to Signal Processing: Exponential Signals (Lecture 3)

20:12

Introduction to Signal Processing: Basic Signals (Lecture 2)

32:24

Introduction to Signal Processing: An Overview (Lecture 1)

23:26

Dimensionally Consistent Learning with Buckingham Pi

29:04

Numerical Integration

34:43

Numerical Differentiation

25:02

Personal Filming Studio

28:31

Eigenfaces

30:11

Eigenvectors and Eigenvalues