Deep learning - Samenvattingen en Aantekeningen

Those are the notes I made during the whole course, it is not a summary! As long as you understand this document you do not need to watch any lecture. With those notes I have passed the course with a 7.5.

This documents contains a summary of the final modules/weeks (4-7) for the course Data Mining for Business and Governance. The following topics are included in this summary: ⋅ Crisp (K-means) clustering ⋅ Fuzzy (c-means) clustering ⋅ Hierarchical clustering ⋅ Text mining ⋅ Preprocessing noisy text ⋅ Document similarity: Jaccard coefficient ⋅ Term frequency, inverse term frequency ⋅ Dimensionality reduction ⋅ Feature selection ⋅ Filtering strategy ⋅ Wrapper s...

The fourth chapter of "Strategy Design" by Birthe Weckx explores various transformative technologies and their impacts on business and society. This chapter is an insightful deep dive into the implications and applications of cutting-edge innovations. Key topics include: 1. **Artificial Intelligence (AI)**: Discusses AI's transformative power across industries, from healthcare to manufacturing, and emphasizes the need for an ethical and collaborative approach to AI integration. 2. **Int...

This is a summary of the paper End-to-end Object Detection with Transformers for the course Seminar of Computer Vision by Deep Learning in TU Delft

This is a summary of the paper Supervised learning based on temporal coding in spiking neural networks for the course Seminar of Computer Vision by Deep Learning in TU Delft

This is a summary of the paper A Metric Learning Reality Check for the course Seminar of Computer Vision by Deep Learning in TU Delft

This is a summary of the paper NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis for the course Seminar of Computer Vision by Deep Learning in TU Delft

This is a summary of the paper On Translation Invariance in CNNs: Convolutional Layers can Exploit Absolute Spatial Location for the course Seminar of Computer Vision by Deep Learning in TU Delft

This is a summary of the paper Masked Autoencoders Are Scalable Vision Learners for the course Seminar of Computer Vision by Deep Learning in TU Delft

This is a summary for the paper Visual Prompt Tuning used for the course Computer Vision by Deep Learning in TU Delft