Exercises for the course Machine Learning 1 Winter semester 2020/21 Abteilung Maschinelles Lernen Institut fu ̈r Softwaretechnik und theoretische Informatik Fakult ̈at IV, Technische Universit…
Machine Learning 1 TU Berlin, WiSe 2020/21 Decision Trees, Random Forests, Boosting (40 P) The goal of this homework is to extend decision trees, using…
Wojciech Samek & Gr¨goire Montavon ML1 Lecture 11: Neural Networks 2 ML1 Lecture 11: Neural Networks 3 ML1 Lecture 11: Neural Networks 4 ML1 Lecture…
lecture/12-em-annotated.pdf lecture/13-poe-annotated.pdf lecture/14-xai-annotated.pdf lecture/lecture1-annotated.pdf lecture/lecture10.pdf lecture/lecture11.pdf 1/24 Outline � Latent Variable Models � The Expectation Maximization Procedure � Gaussian Mixture Models � K-Means Clustering �…
Family name Student ID First name Signature of candidate University of Toronto Electrical and Computer Engineering PA 1 25 2 14 3 12 4 14…
Wojciech Samek & Gr¨goire Montavon ML1 Lecture 10: Kernel Ridge Regression 2 ML1 Lecture 10: Kernel Ridge Regression 3 ML1 Lecture 10: Kernel Ridge Regression…
Lesson 06 – Thread-Level Parallelism: Introduction Introduction Introduction Pipelining became universal technique in 1985 Overlaps execution of instructions Beyond pipelining, Instruction Level Parallelism (ILP)…
Wojciech Samek & Grégoire Montavon About myself 1. Interpretability & Explainability 2. Neural Network Compression 3. Federated Learning 4. Applications of Deep Learning ML1 Lecture…
Machine Learning 1 TU Berlin, WiSe 2020/21 Kernel Support Vector Machines In this exercise sheet, we will implement a kernel SVM. Our implementation will be…
Machine Learning 1 TU Berlin, WiSe 2020/21 In [1]: import numpy,sklearn,sklearn.datasets,utils %matplotlib inline Principal Component Analysis In this exercise, we will experiment with two different…