Alex Smola

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Machine Learning for Everyone

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Lecture 15, Part 3, Axiomatic Explanations

Lecture 15, Part 3, Axiomatic Explanations

Alex Smola

1.3K views·4 years ago

Lecture 15, Part 4, Heuristics

Lecture 15, Part 4, Heuristics

Alex Smola

475 views·4 years ago

Lecture 15, Part 2, Local Models and Conditioning

Lecture 15, Part 2, Local Models and Conditioning

Alex Smola

360 views·4 years ago

Lecture 15, Part 1, Simple Explanations

Lecture 15, Part 1, Simple Explanations

Alex Smola

329 views·4 years ago

Lecture 14, Part 3, Fairness in Practice

Lecture 14, Part 3, Fairness in Practice

Alex Smola

325 views·4 years ago

Lecture 14, Part 2, Fairness and Scores

Lecture 14, Part 2, Fairness and Scores

Alex Smola

295 views·4 years ago

Lecture 14, Part 1, Fairness Background

Lecture 14, Part 1, Fairness Background

Alex Smola

300 views·4 years ago

Lecture 8, Part 4, Graphs and Networks

Lecture 8, Part 4, Graphs and Networks

Alex Smola

652 views·4 years ago

Lecture 8, Part 3 More about Sequence Models

Lecture 8, Part 3 More about Sequence Models

Alex Smola

411 views·4 years ago

Lecture 8, Part 2 Sequence Models

Lecture 8, Part 2 Sequence Models

Alex Smola

388 views·4 years ago

Lecture 8, Part 1 Dependent Random Variables

Lecture 8, Part 1 Dependent Random Variables

Alex Smola

806 views·4 years ago

Lecture 6, Part 2, Covariate Shift

Lecture 6, Part 2, Covariate Shift

Alex Smola

1.3K views·4 years ago

Lecture 6, Part 4, Adversarial Data

Lecture 6, Part 4, Adversarial Data

Alex Smola

336 views·4 years ago

Lecture 6, Part 3, More Math for Covariate Shift

Lecture 6, Part 3, More Math for Covariate Shift

Alex Smola

579 views·4 years ago

Lecture 6, Part 1, Generalization

Lecture 6, Part 1, Generalization

Alex Smola

3.2K views·4 years ago

Lecture 7, Part 2 Label Shift

Lecture 7, Part 2 Label Shift

Alex Smola

1.2K views·4 years ago

Lecture 7, Part 1 - Two-sample tests

Lecture 7, Part 1 - Two-sample tests

Alex Smola

778 views·4 years ago

5.3 BERT and Applications

5.3 BERT and Applications

Alex Smola

1.6K views·5 years ago

5.2 Transformers

5.2 Transformers

Alex Smola

1.8K views·5 years ago

5.1 Attention

5.1 Attention

Alex Smola

3.3K views·5 years ago

4.3 Deep and Bidirectional LSTMs

4.3 Deep and Bidirectional LSTMs

Alex Smola

7.5K views·5 years ago

4.2 LSTM and Friends

4.2 LSTM and Friends

Alex Smola

1.1K views·5 years ago

2.4 Autograd in PyTorch

2.4 Autograd in PyTorch

Alex Smola

1.1K views·5 years ago

2.3 Linear Algebra

2.3 Linear Algebra

Alex Smola

788 views·5 years ago

4.1 Sequence Model Basics

4.1 Sequence Model Basics

Alex Smola

1.5K views·5 years ago

2.2 Data Preprocessing (with Pandas)

2.2 Data Preprocessing (with Pandas)

Alex Smola

682 views·5 years ago

3.2 Object Detection Basics

3.2 Object Detection Basics

Alex Smola

1.7K views·5 years ago

3.1 Preprocessing and Transfer Learning

3.1 Preprocessing and Transfer Learning

Alex Smola

728 views·5 years ago

2.3 Modern Convnets (ResNet, NiN, Inception, ShuffleNet, etc.)

2.3 Modern Convnets (ResNet, NiN, Inception, ShuffleNet, etc.)

Alex Smola

2.2K views·5 years ago

2.2 LeNet and AlexNet

2.2 LeNet and AlexNet

Alex Smola

2.1K views·5 years ago

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