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experts
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Multi-Task Learning package built with tensorflow 2 (Multi-Gate Mixture of Experts, Cross-Stitch, Ucertainty Weighting)
keras
experts
multi-task-learning
cross-stitch
multitask-learning
kdd2018
mixture-of-experts
tensorflow2
recsys2019
papers-with-code
papers-reproduced
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Jan 20, 2020 - Python
ML-AI Community | Open Source | Built in Bharat for the World | Data science problem statements and solutions
data-science
machine-learning
deep-neural-networks
reinforcement-learning
deep-learning
neural-network
tensorflow
machine-learning-algorithms
academic
artificial-intelligence
supervised-learning
reinforcement-learning-algorithms
india
experts
unsupervised-learning
neural
industry
teach
bharat
academic-researchers
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May 8, 2020 - Jupyter Notebook
Network of Experts for Large-Scale Image Categorization [ECCV 2016]
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Jul 22, 2019 - C++
Gaussian Parsimonious Clustering Models with Gating and Expert Network Covariates
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May 12, 2020 - R
Write-ups for TheNewStack
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Jul 2, 2019
Data collection, analysis and regression of luxury hand bag prices
python
deep-learning
presentation
linear-regression
scikit-learn
domain-driven-design
regression
cnn
pandas
fuzzy
data-collection
experts
feature-engineering
ridge-regression
lasso-regression
mlp-regressor
ensemble-machine-learning
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Updated
Jan 25, 2019 - Python
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#196 introduced a double up of each entry that wasn't caught in review. In order to prevent repeat cases of this, or minor double ups, a Github actions entry should be created that checks for any double ups of the program name at the time when a new pull request is created, and if so, fail the case.