CS480/680 Lecture 19: Attention and Transformer Networks

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CS480/680 Lecture 1: Course Introduction

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CS480/680 Lecture 5: Statistical Linear Regression

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CS480/680 Lecture 6: Fact checking and reinforcement learning (Vik Goel)

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CS480/680 Lecture 15: Deep neural networks

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CS480/680 Lecture 16: Convolutional neural networks

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Stanford CS224N NLP with Deep Learning | 2023 | Lecture 8 - Self-Attention and Transformers

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CS480/680 Lecture 23: Normalizing flows (Priyank Jaini)

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CS480/680 Lecture 11: Kernel Methods

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MegaScan USD Builder / Batch Convert to USD wip

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CS480/680 Lecture 13: Support vector machines

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Deep Learning Full Course - Learn Deep Learning in 6 Hours | Deep Learning Tutorial | Edureka

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CS480/680 Lecture 8: Logistic regression and generalized linear models

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CS480/680 Lecture 7: Mixture of Gaussians

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Lecture 9 | CNN Architectures

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CS480/680 Lecture 17: Hidden Markov Models

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CS480/680 Lecture 12: Gaussian Processes

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CS480/680 Lecture 18: Recurrent and recursive neural networks

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CS480/680 Lecture 6: Kaggle datasets and competitions

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CS480/680 Lecture 6: Model compression for NLP (Ashutosh Adhikari)

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CS480/680 Lecture 22: Ensemble learning (bagging and boosting)

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CS480/680 Lecture 20: Autoencoders

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CS480/680 Lecture 6: Unsupervised word translation (Kira Selby)

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CS480/680 Lecture 6: Tools for surveys (Paulo Pacheco)

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CS480/680 Lecture 14: Support vector machines (continued)

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CS480/680 Lecture 9: Perceptrons and single layer neural nets

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CS480/680 Lecture 3: Linear Regression

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