Lesson type
Difficulty level
Introduction of the Foundations of Machine Learning in Python course - Day 01.
High-Performance Computing and Analytics Lab, University of Bonn
Difficulty level: Beginner
Duration: 35:24
Speaker: : Elena Trunz
Optimization for machine learning - Day 02 lecture of the Foundations of Machine Learning in Python course.
High-Performance Computing and Analytics Lab, University of Bonn
Difficulty level: Advanced
Duration: 34:52
Speaker: : Moritz Wolter
Linear Algebra for Machine Learning - Day 03 lecture of the Foundations of Machine Learning in Python course.
High-Performance Computing and Analytics Lab, University of Bonn
Difficulty level: Advanced
Duration: 57.45
Speaker: : Moritz Wolter
Support Vector Machines - Day 06 lecture of the Foundations of Machine Learning in Python course.
High-Performance Computing and Analytics Lab, University of Bonn
Difficulty level: Advanced
Duration: 53.39
Speaker: : Elena Trunz
Decision Trees and Random Forests - Day 07 lecture of the Foundations of Machine Learning in Python course.
High-Performance Computing and Analytics Lab, University of Bonn
Difficulty level: Advanced
Duration: 1:15:39
Speaker: : Elena Trunz
Clustering and Density Estimation - Day 08 lecture of the Foundations of Machine Learning in Python course.
High-Performance Computing and Analytics Lab, University of Bonn
Difficulty level: Advanced
Duration: 59:35
Speaker: : Elena Trunz
Dimensionality Reduction - Day 09 lecture of the Foundations of Machine Learning in Python course.
High-Performance Computing and Analytics Lab, University of Bonn
Difficulty level: Advanced
Duration: 51:02
Speaker: : Elena Trunz
Introduction to Neural Networks - Day 10 lecture of the Foundations of Machine Learning in Python course.
High-Performance Computing and Analytics Lab, University of Bonn
Difficulty level: Advanced
Duration: 54:12
Speaker: : Moritz Wolter
Introduction to Convolutional Neural Networks - Day 11 lecture of the Foundations of Machine Learning in Python course.
High-Performance Computing and Analytics Lab, University of Bonn
Difficulty level: Advanced
Duration: 42:07
Speaker: : Moritz Wolter
Initialization, Optimization, and Regularization - Day 12 lecture of the Foundations of Machine Learning in Python course.
High-Performance Computing and Analytics Lab, University of Bonn
Difficulty level: Advanced
Duration: 42:07
Speaker: : Moritz Wolter
U-Nets for medical Image-Segmentation - Day 13 lecture of the Foundations of Machine Learning in Python course.
High-Performance Computing and Analytics Lab, University of Bonn
Difficulty level: Advanced
Duration: 16:45
Speaker: : Moritz Wolter
Sequence Processing - Day 15 lecture of the Foundations of Machine Learning in Python course.
High-Performance Computing and Analytics Lab, University of Bonn
Difficulty level: Advanced
Duration: 47:45
Speaker: : Moritz Wolter
In this lesson, you will learn about the current challenges facing the integration of machine learning and neuroscience.
Difficulty level: Beginner
Duration: 5:42
Speaker: : Dan Goodman
Course:
This lesson provides a brief overview of the Python programming language, with an emphasis on tools relevant to data scientists.
Difficulty level: Beginner
Duration: 1:16:36
Speaker: : Tal Yarkoni
This tutorial covers the fundamentals of collaborating with Git and GitHub.
Difficulty level: Intermediate
Duration: 2:15:50
Speaker: : Elizabeth DuPre
Course:
The lecture provides an overview of the core skills and practical solutions required to practice reproducible research.
Difficulty level: Beginner
Duration: 1:25:17
Speaker: : Fernando Perez
This lecture covers the description and brief history of data science and its use in neuroinformatics.
Difficulty level: Beginner
Duration: 11:15
Speaker: : Ariel Rokem
This lesson provides an overview of self-supervision as it relates to neural data tasks and the Mine Your Own vieW (MYOW) approach.
Difficulty level: Beginner
Duration: 25:50
Speaker: : Eva Dyer