Schedule
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EventDateDescriptionCourse Material
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Lecture01/12/2023
ThursdayLecture 1 Course Introduction[Notes] -
Lecture01/17/2023
TuesdayLecture 2 Singular Value Decomposition (SVD)[Notes]Suggested Readings:
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Lecture01/19/2023
ThursdayLecture 3 Image Compression with SVD[Notes]Suggested Readings:
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Assignment01/24/2023
TuesdayHomework 1 released! -
Lecture01/24/2023
TuesdayLecture 4 Image Encoding[Notes]Suggested Readings:
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Lecture01/26/2023
ThursdayLecture 5 Principal Component Analysis (PCA)[Notes]Suggested Readings:
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Lecture01/31/2023
TuesdayLecture 6 PCA II[Notes] -
Lecture02/02/2023
ThursdayLecture 7 PCA III[Notes] -
Lecture02/07/2023
TuesdayLecture 8 Neural Networks[Notes] -
Lecture02/09/2023
ThursdayLecture 9 Autoencoders[Notes]Suggested Readings:
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Lecture02/14/2023
TuesdayLecture 10 Autoencoders II[Notes]Suggested Readings:
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Due02/14/2023 23:59
TuesdayHomework 1 due -
Lecture02/21/2023
TuesdayLecture 12 Probabilistic PCA[Notes] -
Lecture02/23/2023
ThursdayLecture 13 Probabilistic PCA II[Notes]Suggested Readings:
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Lecture02/28/2023
TuesdayLecture 14 Probabilistic PCA III[Notes] -
Lecture03/02/2023
ThursdayLecture 15 Variational Autoencoders I[Notes]Suggested Readings:
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Lecture03/07/2023
TuesdayLecture 16 Variational Autoencoders II[Notes] -
Lecture03/23/2023
ThursdayLecture 19 Variational Autoencoders III[Notes] -
Lecture03/28/2023
TuesdayLecture 20 Variational Autoencoders IV[Notes]Suggested Readings:
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Lecture03/30/2023
ThursdayLecture 21 Variational Autoencoders V[Notes]Suggested Readings:
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Lecture04/06/2023
ThursdayLecture 23 VAE conclusionSuggested Readings:
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Lecture04/13/2023
ThursdayLecture 24 Gradient Descent for Deep Learning I[Notes] -
Lecture04/18/2023
TuesdayLecture 25 Gradient Descent for Deep Learning II[Notes] -
Lecture04/20/2023
ThursdayLecture 26 Gradient Descent for Deep Learning IIISuggested Readings: