BIBA - Clustering - Deep Neural Networks
9 important questions on BIBA - Clustering - Deep Neural Networks
What is a deep neural netowrk?
What is the advantage of Deep learning in contrast to Machine learning?
- In ML you always need to know the predictor, however in DL we expect something to predict something else and you can run the model. The back propagation makes sure the model learns and it can handle large amount of data.
- Can handle large amount of data
- High predictive performance
Why does a DL model starts to overfit at one point and how do you counter this?
Overfitting regularization:
- Early stopping
- Drop out regularization
- L1/L2 regularization
- Higher grades + faster learning
- Never study anything twice
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What is a convolutional neural network (CNN)?
How does a convulational layers calculates based on the input image?
What does the pooling layer?
What is max pooling and average pooling?
Average pooling: take the average value of filter per section
What type of learning is used in Convolutional Neural Network and is the implication?
- Supervised learning, data labeling (e.g. Selfdriving car: people on the street, other cars etc,)
- If you input labeled data not well, the output will be bad as well.
- Unsupervised learning, find patterns in data, don't need labels.
What are challenges within convolutional neural network?
- Ground truth / missing labels (expert labeling)
- Transparency
- Unbalanced datasets
The question on the page originate from the summary of the following study material:
- A unique study and practice tool
- Never study anything twice again
- Get the grades you hope for
- 100% sure, 100% understanding
