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08:50
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Organisational
-
Ulrik Egede
(Imperial College (GB))
Andrey Ustyuzhanin
(Yandex School of Data Analysis (RU))
(until 09:00)
(Reading University)
|
|
08:50
|
'Welcome to MLHEP' Opening Words
-
Ulrik Egede
(Imperial College (GB))
Andrey Ustyuzhanin
(Yandex School of Data Analysis (RU))
(Reading University)
|
|
09:00
|
Lectures
-
Alexey Artemov
(Yandex)
(until 10:30)
(Reading University)
|
|
09:00
|
Lecture 1. Introduction. Why ML works. Overfitting. Model Selection. Figures of Merits. Linear Models. Regularization. Logistic Regression.
-
Alexey Artemov
(Yandex)
(Reading University)
|
|
10:30
|
--- Coffee break ---
|
|
10:50
|
Practice: challenge & industry
-
Andrey Ustyuzhanin
(Yandex School of Data Analysis (RU))
(until 11:10)
(Reading University)
|
|
10:50
|
Competition Introduction
-
Andrey Ustyuzhanin
(Yandex School of Data Analysis (RU))
(Reading University)
|
|
11:10
|
Seminars
-
Alexander Panin
(Yandex School of Data Analysis (RU))
(until 12:40)
(Reading University)
|
|
11:10
|
Seminar 1. Python data crunching: numpy, root_numpy, pandas (very short), matplotlib.
-
Alexander Panin
(Yandex School of Data Analysis (RU))
(Reading University)
|
|
|
09:00
|
Lectures
(until 10:30)
(Reading University)
|
|
09:00
|
Lecture 3. Ensembling: Adaboost, Stacking. Gradient Boosting.
(Reading University)
|
|
10:30
|
--- Coffee break ---
|
|
11:00
|
Seminars
(until 12:30)
(Reading University)
|
|
11:00
|
Seminar 3. Ensembling: Adaboost, Stacking. Gradient Boosting.
(Reading University)
|
|
|
09:00
|
Free day
(until 21:00)
(Reading University)
|
|
|
09:00
|
Lectures
(until 10:30)
(Reading University)
|
|
09:00
|
Lecture 5. Introduction into Neural Network models. Multi-layered Perceptron. Backpropagation.
(Reading University)
|
|
10:30
|
--- Coffee break ---
|
|
11:00
|
Seminars
(until 12:30)
(Reading University)
|
|
11:00
|
Seminar 5. Computing gradient by hand. Tensorflow. Keras. Remote machine setup. Getting familiar with GPU.
(Reading University)
|
|
|
09:00
|
Practice: challenge & industry
(until 10:30)
(Reading University)
|
|
10:30
|
--- Coffee break ---
|
|
11:00
|
Practice: challenge & industry
(until 12:30)
(Reading University)
|
|
|
09:00
|
Lectures
(until 10:30)
(Reading University)
|
|
09:00
|
Lecture 8 Generative Adversarial Networks, Metric Learning.
(Reading University)
|
|
10:30
|
--- Coffee break ---
|
|
11:00
|
Seminars
(until 12:30)
(Reading University)
|
|
11:00
|
Seminar 8 Generative Adversarial Networks (physics)
(Reading University)
|
|
|
09:00
|
Lecture 10. Why Deep Learning works. Tips & tweaks.
(Reading University)
|
|
10:30
|
--- Break ---
|
|
11:00
|
Practice: challenge & industry
(until 12:00)
(Reading University)
|
|
|
12:40
|
Organisational
(until 14:00)
(Reading University)
|
|
14:00
|
Lectures
-
Alexey Artemov
(Yandex)
(until 15:30)
(Reading University)
|
|
14:00
|
Lecture 2. Decision Trees. Bagging. Ensembles. RandomForest. AdaBoost. GB-Reweighting. Gradient Boosting. Decorrelation of features with predictions.
-
Alexey Artemov
(Yandex)
(Reading University)
|
|
15:30
|
--- Coffee break ---
|
|
15:50
|
Seminars
-
Alexander Panin
(Yandex School of Data Analysis (RU))
(until 17:20)
(Reading University)
|
|
15:50
|
Seminar 2. Matplotlib, Trees & Linear Models in SciKit Learn. Overfitting checks & prevention.
-
Alexander Panin
(Yandex School of Data Analysis (RU))
(Reading University)
|
|
19:00
|
Organisational
(until 20:30)
(Reading University)
|
|
|
12:30
|
Organisational
(until 13:30)
(Reading University)
|
|
13:30
|
Lectures
(until 15:00)
(Reading University)
|
|
13:30
|
Lecture 4. Hyperparameters optimization techniques and methods. Feature selection. TPE. Gaussian Processes
(Reading University)
|
|
15:00
|
--- Coffee break ---
|
|
15:30
|
Seminars
(until 17:00)
(Reading University)
|
|
15:30
|
Seminar 4. Optimization of hyper-parameters, applications to challenge.
(Reading University)
|
|
17:00
|
Organisational
(until 17:15)
(Reading University)
|
|
17:15
|
Invited lectures
(until 18:45)
(Reading University)
|
|
|
|
12:30
|
Organisational
(until 13:30)
(Reading University)
|
|
13:30
|
Lectures
(until 15:00)
(Reading University)
|
|
13:30
|
Lecture 6. Intro into Deep learning. Convolutional Neural Network. Model zoo. Augmentation.
(Reading University)
|
|
15:00
|
--- Coffee break ---
|
|
15:30
|
Seminars
(until 17:00)
(Reading University)
|
|
15:30
|
Seminar 6. Image recognition using convolutional neural networks.
(Reading University)
|
|
17:00
|
Organisational
(until 17:15)
(Reading University)
|
|
17:15
|
Invited lectures
(until 18:45)
(Reading University)
|
|
17:15
|
Guest Lecture
-
Noel Dawe
(University of Melbourne (AU))
(Reading University)
|
|
|
12:30
|
Organisational
(until 13:30)
(Reading University)
|
|
13:30
|
Lectures
(until 15:00)
(Reading University)
|
|
13:30
|
Lecture 7. Dimensionality Reduction. PCA. LDA. LLE. TSNE. Autoencoders.
(Reading University)
|
|
15:00
|
--- Coffee break ---
|
|
15:30
|
Seminars
(until 17:00)
(Reading University)
|
|
15:30
|
Seminar 7. PCA, Autoencoders (faces)
(Reading University)
|
|
17:00
|
Organisational
(until 17:15)
(Reading University)
|
|
17:15
|
Invited lectures
(until 18:45)
(Reading University)
|
|
19:00
|
--- Dinner ---
|
|
|
12:30
|
Organisational
(until 13:30)
(Reading University)
|
|
13:30
|
Lectures
(until 16:00)
(Reading University)
|
|
13:30
|
Lecture 9. RNNs.
(Reading University)
|
|
15:00
|
--- Coffee break ---
|
|
15:30
|
Certificates, Free Discussion
(Reading University)
|
|
|
