Sixth Machine Learning in High Energy Physics Summer School 2020

Session

Section 1. Introduction into ML

16 Jul 2020, 11:30

Zoom

Conveners

Section 1. Introduction into ML: Basics

• Artem Maevskiy (National Research University Higher School of Economics (RU))

Section 1. Introduction into ML: Linear Regression

• Artem Maevskiy (National Research University Higher School of Economics (RU))

Section 1. Introduction into ML: Logistic regression-1

• Artem Maevskiy (National Research University Higher School of Economics (RU))

Section 1. Introduction into ML: Logistic regression-2

• Artem Maevskiy (National Research University Higher School of Economics (RU))

Section 1. Introduction into ML: Quality Metrics-1

• Mikhail Hushchyn (Yandex School of Data Analysis (RU))

Section 1. Introduction into ML: Quality Metrics-2

• Mikhail Hushchyn (Yandex School of Data Analysis (RU))

Section 1. Introduction into ML: Decision trees-1

• Nikita Kazeev (Yandex School of Data Analysis (RU))

Section 1. Introduction into ML: Ensembles-1

• Nikita Kazeev (Yandex School of Data Analysis (RU))

Section 1. Introduction into ML: Ensembles-2

• Nikita Kazeev (Yandex School of Data Analysis (RU))

Section 1. Introduction into ML: Useful hacks.

• Mikhail Hushchyn (Yandex School of Data Analysis (RU))

Section 1. Introduction into ML: Clustering-1

• Mikhail Hushchyn (Yandex School of Data Analysis (RU))

Section 1. Introduction into ML: Clustering-2

• Mikhail Hushchyn (Yandex School of Data Analysis (RU))

99. Introduction into supervised learning

Artem Maevskiy (National Research University Higher School of Economics (RU))

16/07/2020, 11:30

Practical session

113. Seminar: Data Handling in Python

Artem Maevskiy (National Research University Higher School of Economics (RU))

16/07/2020, 12:00

100. Linear Regression

Artem Maevskiy (National Research University Higher School of Economics (RU))

16/07/2020, 13:30

Linear regression. Analytical solution. Gradient descent. Numerical solution. Polynomial features.

114. Seminar

Artem Maevskiy (National Research University Higher School of Economics (RU))

16/07/2020, 14:00

101. Logistic regression-1

Artem Maevskiy (National Research University Higher School of Economics (RU))

16/07/2020, 15:00

115. Seminar

16/07/2020, 15:30

102. Logistic regression-2

Artem Maevskiy (National Research University Higher School of Economics (RU))

16/07/2020, 16:30

Linear models regularization. Probabilistic interpretation of linear models (regression and classification).

116. Seminar

Artem Maevskiy (National Research University Higher School of Economics (RU))

16/07/2020, 17:00

103. Quality Metrics-1

Mikhail Hushchyn (Yandex School of Data Analysis (RU))

17/07/2020, 09:00

Quality metrics for classification and regression

118. Seminar: Quality Metrics-1

17/07/2020, 09:30

104. Quality Metrics-2

Mikhail Hushchyn (Yandex School of Data Analysis (RU))

17/07/2020, 10:30

How to test your model. Cross validation. Statistical model comparison

119. Seminar: Quality Metrics-2

Mikhail Hushchyn (Yandex School of Data Analysis (RU))

17/07/2020, 11:00

105. Decision trees-1

Mr Nikita Kazeev (Yandex School of Data Analysis (RU))

17/07/2020, 12:00

Splitting rule. Classification and regression decision trees

120. Seminar: Decision trees-1

Nikita Kazeev (Yandex School of Data Analysis (RU))

17/07/2020, 12:30

107. Ensembles-1

Nikita Kazeev (Yandex School of Data Analysis (RU))

17/07/2020, 14:00

Bagging and Random Forest. Stacking and blending.

122. Seminar: Ensembles-1

Nikita Kazeev (Yandex School of Data Analysis (RU))

17/07/2020, 14:30

112. Ensembles-2

Nikita Kazeev (Yandex School of Data Analysis (RU))

17/07/2020, 15:30

Gradient boosting.

123. Seminar: Ensembles-2

Nikita Kazeev (Yandex School of Data Analysis (RU))

17/07/2020, 16:00

109. Useful hacks

Mikhail Hushchyn (Yandex School of Data Analysis (RU))

18/07/2020, 09:00

Feature engineering, importance and selection.

124. Seminar: Useful hacks.

Mikhail Hushchyn (Yandex School of Data Analysis (RU))

18/07/2020, 09:30

110. Clustering-1

Mikhail Hushchyn (Yandex School of Data Analysis (RU))

18/07/2020, 10:30

Clustering. K-Means. Quality metrics for clustering

125. Seminar: Clustering-1

Mikhail Hushchyn (Yandex School of Data Analysis (RU))

18/07/2020, 11:00

111. Clustering-2

Mikhail Hushchyn (Yandex School of Data Analysis (RU))

18/07/2020, 12:00

Hierarchical clustering and DBSCAN.

126. Seminar: Clustering-2

Mikhail Hushchyn (Yandex School of Data Analysis (RU))

18/07/2020, 12:30

106. Decision trees-2

Nikita Kazeev (Yandex School of Data Analysis (RU))

121. Seminar: Decision trees-2