-
https://towardsdatascience.com/deep-metric-learning-76fa0a5a415f
Similar to k-nearest neighbor:
1. Train an encoder to encode raw data into a feature space.
2. Data points belonging to the same/d…
-
Although other learning algorithms implemented in H2O already offer MCC metric, such as GLM, the MCC metric is not currently available for the deep learning algorithm in H2O. For highly unbalanced, e…
-
1. [Intro/survey on Deep Metric Learning](https://www.mdpi.com/2073-8994/11/9/1066/htm) ([blogpost](https://hav4ik.github.io/articles/deep-metric-learning-survey))
2. [Improved Deep Metric Learning w…
-
https://arxiv.org/abs/1412.6622
-
### Deep Learning Simplified Repository (Proposing new issue)
:red_circle: **Project Title** : Predicting IPO Performance Using Deep Learning
:red_circle: **Aim** :This project aims to predict the p…
-
### Feature Description
Hi,
In TensorFlow Addons there are many [Deep Metrics Learning (DML) losses](https://www.tensorflow.org/addons/api_docs/python/tfa/losses) been implemented (such as tripl…
-
https://arxiv.org/abs/1908.10192
-
Hi, I am walking through the experiments via codes, and find hard to understand the result of Figure 3 in "Penalizing Gradient Norm for Efficiently Improving Generalization in Deep Learning".
In …
-
### Description
Incorporate machine learning models to enhance the classification of movements and prediction of performance. This will enable more sophisticated analysis and provide deeper insights …
-
○ Time: 6 weeks
○ Tools Required: Scikit-learn, TensorFlow, PyTorch (within Azure AI Studio or Microsoft Fabric)
○ Steps:
1. Define model requirements and objectives.
□ Utilize histor…
zepor updated
4 weeks ago