Seventh Machine Learning in High Energy Physics Summer School 2021

Session

Section 1. Introduction into ML

15 Jul 2021, 13:30

Zoom

Conveners

Section 1. Introduction into ML: Data handling in Python

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

Section 1. Introduction into ML: Ensembles-1

• Nikita Kazeev (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: Quality Metrics-2

• 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: Useful hacks.

• Mikhail Hushchyn (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: Quality Metrics-1

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

Section 1. Introduction into ML: Logistic regression-2

• 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: Linear Regression

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

Section 1. Introduction into ML: Clustering-2

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

110. Clustering-1

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

Clustering. K-Means. Quality metrics for clustering

111. Clustering-2

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

Hierarchical clustering and DBSCAN.

187. Coopetition introduction (1)

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

105. Decision trees-1

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

Splitting rule. Classification and regression decision trees

106. Decision trees-2

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

107. Ensembles-1

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

Bagging and Random Forest. Stacking and blending.

112. Ensembles-2

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

Gradient boosting.

99. Introduction into supervised learning

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

Practical session

100. Linear Regression

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

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

101. Logistic regression-1

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

102. Logistic regression-2

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

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

103. Quality Metrics-1

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

Quality metrics for classification and regression

104. Quality Metrics-2

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

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

116. Seminar

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

115. Seminar

114. Seminar

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

125. Seminar: Clustering-1

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

126. Seminar: Clustering-2

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

113. Seminar: Data Handling in Python

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

120. Seminar: Decision trees-1

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

121. Seminar: Decision trees-2

122. Seminar: Ensembles-1

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

123. Seminar: Ensembles-2

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

118. Seminar: Quality Metrics-1

119. Seminar: Quality Metrics-2

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

124. Seminar: Useful hacks.

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

109. Useful hacks

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

Feature engineering, importance and selection.