#9 Image Denoising problem using Gateaux Derivative
4th November, 2023
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TUM: Variational Calculus (Chapter 3), Lecture Notes, Prof. Daniel Cremers (2019)
#8 Linear Least Squares with the directional derivative
1st November, 2023
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Convex Optimization, Textbook, Stephen P. Boyd & Lieven Vandenberghe
#7 MNIST Neural Net with Backpropagation from scratch
28th September, 2023
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CS231n Lecture Notes, Andrej Karpathy, Li Fei-Fei (2016)
CS229 Lecture Notes, Andrew Ng and Tengyu Ma (2023)
#6 Gaussian Discriminative Analysis (GDA)
19th August, 2023
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STAT 260: Bayesian Modeling and Inference (Chapter 13), Michael I. Jordan (2010)
CS229 Lecture Notes, Andrew Ng and Tengyu Ma (2023)
#5 Maximizing the Log Likelihood Estimator in Logistic Regression
15th August, 2023
- CS229 Lecture Notes, Andrew Ng and Tengyu Ma (2023)
#4 Solving the Linear Mean Squares problem on Linear Regression
13th August, 2023
- CS229 Lecture Notes, Andrew Ng and Tengyu Ma (2023)
#3 Support Vectors Machines from the ground up
9th August, 2023
- MIT 6.034 - Artificial Intelligence. Lecture 16: Learning: Support Vector Machines, Patrick H. Winston (2010)
#2 Solving the Least Squares problem on Linear Regression
3rd August, 2023
- Probabilistic Machine Learning: An Introduction, Kevin P. Murphy (2022)
- MLPR 2022: Regression and Gradients (Notes), University of Edinburgh (2022)
#1 Solving the Gradient with the Normal Equations
28th July, 2023
- Deep Learning Book, Ian Goodfellow and Yoshua Bengio and Aaron Courville (2016)
- Differential Calculus Theory, CS224N, Stanford (2022)