Real-Time Face Mask Detector with Python, OpenCV, Keras
https://data-flair.training/blogs/face-mask-detection-with-python/
Dataset: https://data-flair.training/blogs/download-face-mask-data/
Code: https://data-flair.training/blogs/download-face-mask-detector-project-source-code/
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https://data-flair.training/blogs/face-mask-detection-with-python/
Dataset: https://data-flair.training/blogs/download-face-mask-data/
Code: https://data-flair.training/blogs/download-face-mask-detector-project-source-code/
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DataFlair
Real-Time Face Mask Detector with Python, OpenCV, Keras - DataFlair
Real-time Face Mask Detector with Python - develop a real-time system to detect whether the person on the webcam is wearing a mask or not. We train the face mask detection model using Keras and OpenCV.
Multi-scale Interactive Network for Salient Object Detection.
Github: https://github.com/lartpang/MINet
Paper: https://arxiv.org/abs/2007.09062v1
Results & Pretrained Parameters: https://drive.google.com/drive/folders/16yTcf_m-ehnhWgXlN6hbZpBKMy6lYIQQ
Github: https://github.com/lartpang/MINet
Paper: https://arxiv.org/abs/2007.09062v1
Results & Pretrained Parameters: https://drive.google.com/drive/folders/16yTcf_m-ehnhWgXlN6hbZpBKMy6lYIQQ
Private prediction methods: A systematic study by Facebook Research
https://ai.facebook.com/blog/private-prediction-methods-a-systematic-study/
Github: https://github.com/facebookresearch/private_prediction
Paper: https://arxiv.org/pdf/2007.05089.pdf
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https://ai.facebook.com/blog/private-prediction-methods-a-systematic-study/
Github: https://github.com/facebookresearch/private_prediction
Paper: https://arxiv.org/pdf/2007.05089.pdf
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Meta
Private prediction methods: A systematic study
The first systematic study of the performance of all main private prediction techniques in realistic machine learning (ML) scenarios. This study is meant to help solve…
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Using Snorkel and NLP Models to Predict Multiple Sclerosis Severity Scores
https://www.kdnuggets.com/2020/07/labelling-data-using-snorkel.html
Tutorial: https://nlp4h.com/blog/snorkel_tutorial/
https://www.kdnuggets.com/2020/07/labelling-data-using-snorkel.html
Tutorial: https://nlp4h.com/blog/snorkel_tutorial/
KDnuggets
Labelling Data Using Snorkel - KDnuggets
In this tutorial, we walk through the process of using Snorkel to generate labels for an unlabelled dataset. We will provide you examples of basic Snorkel components by guiding you through a real clinical application of Snorkel.
Whole-Body Human Pose Estimation in the Wild
Github: https://github.com/jin-s13/COCO-WholeBody
Paper: https://arxiv.org/abs/2007.11858v1
Dataset: https://cocodataset.org/#keypoints-2017
Github: https://github.com/jin-s13/COCO-WholeBody
Paper: https://arxiv.org/abs/2007.11858v1
Dataset: https://cocodataset.org/#keypoints-2017
LOOCV for Evaluating Machine Learning Algorithms
https://machinelearningmastery.com/loocv-for-evaluating-machine-learning-algorithms/
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https://machinelearningmastery.com/loocv-for-evaluating-machine-learning-algorithms/
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DeepSVG
A Hierarchical Generative Network for Vector Graphics Animation.
https://blog.alexandrecarlier.com/deepsvg/
Github: https://github.com/alexandre01/deepsvg
Paper: https://arxiv.org/abs/2007.11301
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A Hierarchical Generative Network for Vector Graphics Animation.
https://blog.alexandrecarlier.com/deepsvg/
Github: https://github.com/alexandre01/deepsvg
Paper: https://arxiv.org/abs/2007.11301
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GitHub
GitHub - alexandre01/deepsvg: [NeurIPS 2020] Official code for the paper "DeepSVG: A Hierarchical Generative Network for Vector…
[NeurIPS 2020] Official code for the paper "DeepSVG: A Hierarchical Generative Network for Vector Graphics Animation". Includes a PyTorch library for deep learning with SVG data. ...
TensorFlow 2.3.0 Release
TensorFlow 2.3 has been released!
https://blog.tensorflow.org/2020/07/whats-new-in-tensorflow-2-3.html
Release : https://github.com/tensorflow/tensorflow/releases
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TensorFlow 2.3 has been released!
https://blog.tensorflow.org/2020/07/whats-new-in-tensorflow-2-3.html
Release : https://github.com/tensorflow/tensorflow/releases
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blog.tensorflow.org
What's new in TensorFlow 2.3?
TensorFlow 2.3 has been released with new tools to make it easier to load and preprocess data, and solve input-pipeline bottlenecks.
👶 BabyAI 1.1
BabyAI is a platform used to study the sample efficiency of grounded language acquisitio
Github: https://github.com/mila-iqia/babyai
https://github.com/mila-iqia/babyai
Paper: https://arxiv.org/abs/2007.12770v1
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BabyAI is a platform used to study the sample efficiency of grounded language acquisitio
Github: https://github.com/mila-iqia/babyai
https://github.com/mila-iqia/babyai
Paper: https://arxiv.org/abs/2007.12770v1
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GitHub
GitHub - mila-iqia/babyai: BabyAI platform. A testbed for training agents to understand and execute language commands.
BabyAI platform. A testbed for training agents to understand and execute language commands. - mila-iqia/babyai
Building a Content-Based Book Recommendation Engine
https://www.kdnuggets.com/2020/07/building-content-based-book-recommendation-engine.html
Content-Based Recommendation System using Word Embeddings: https://medium.com/towards-artificial-intelligence/content-based-recommendation-system-using-word-embeddings-c1c15de1ef95
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https://www.kdnuggets.com/2020/07/building-content-based-book-recommendation-engine.html
Content-Based Recommendation System using Word Embeddings: https://medium.com/towards-artificial-intelligence/content-based-recommendation-system-using-word-embeddings-c1c15de1ef95
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KDnuggets
Building a Content-Based Book Recommendation Engine
In this blog, we will see how we can build a simple content-based recommender system using Goodreads data.
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SipMask: Spatial Information Preservation for Fast Image and Video Instance Segmentation
Github: https://github.com/JialeCao001/SipMask
Paper: https://arxiv.org/abs/2007.14772v1
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Github: https://github.com/JialeCao001/SipMask
Paper: https://arxiv.org/abs/2007.14772v1
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On the Convergence of Tsetlin Machines for the IDENTITY- and NOT Operators
The Tsetlin Machine solves complex pattern recognition problems with easy-to-interpret propositional formulas.
Github: https://github.com/cair/TsetlinMachine
Paper: https://arxiv.org/abs/2007.14268v1
The Tsetlin Machine solves complex pattern recognition problems with easy-to-interpret propositional formulas.
Github: https://github.com/cair/TsetlinMachine
Paper: https://arxiv.org/abs/2007.14268v1
Train your TensorFlow model on Google Cloud using TensorFlow Cloud
https://blog.tensorflow.org/2020/08/train-your-tensorflow-model-on-google.html
https://blog.tensorflow.org/2020/08/train-your-tensorflow-model-on-google.html
blog.tensorflow.org
Train your TensorFlow model on Google Cloud using TensorFlow Cloud
The TensorFlow Cloud repository provides APIs that will allow you to easily go from debugging and training your Keras and TensorFlow code in a local environment to distributed training in the cloud.
How to Use XGBoost for Time Series Forecasting
https://machinelearningmastery.com/xgboost-for-time-series-forecasting/
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https://machinelearningmastery.com/xgboost-for-time-series-forecasting/
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Netflix’s Polynote is a New Open Source Framework to Build Better Data Science Notebooks
Polynote is an experimental polyglot notebook environment. Currently, it supports Scala and Python, SQL, and Vega.
https://www.kdnuggets.com/2020/08/netflix-polynote-open-source-framework-better-data-science-notebooks.html
Project page: https://polynote.org/
Github: https://github.com/polynote/polynote
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Polynote is an experimental polyglot notebook environment. Currently, it supports Scala and Python, SQL, and Vega.
https://www.kdnuggets.com/2020/08/netflix-polynote-open-source-framework-better-data-science-notebooks.html
Project page: https://polynote.org/
Github: https://github.com/polynote/polynote
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Multilingual Speech Synthesis
Synthesized samples, training and evaluation data, source code, and parameters for Multilingual Speech Synthesis.
Github: https://github.com/Tomiinek/Multilingual_Text_to_Speech
Demo Code: https://colab.research.google.com/github/Tomiinek/Multilingual_Text_to_Speech/blob/master/notebooks/code_switching_demo.ipynb
Website with samples: https://tomiinek.github.io/multilingual_speech_samples/
Paper: https://arxiv.org/abs/2008.00768
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Synthesized samples, training and evaluation data, source code, and parameters for Multilingual Speech Synthesis.
Github: https://github.com/Tomiinek/Multilingual_Text_to_Speech
Demo Code: https://colab.research.google.com/github/Tomiinek/Multilingual_Text_to_Speech/blob/master/notebooks/code_switching_demo.ipynb
Website with samples: https://tomiinek.github.io/multilingual_speech_samples/
Paper: https://arxiv.org/abs/2008.00768
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Metrics to Use to Evaluate Deep Learning Object Detectors.
https://www.kdnuggets.com/2020/08/metrics-evaluate-deep-learning-object-detectors.html
A Survey on Performance Metrics for Object-Detection Algorithms: https://www.researchgate.net/publication/343194514_A_Survey_on_Performance_Metrics_for_Object-Detection_Algorithms
Github: https://github.com/ultralytics/yolov3/issues/898
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https://www.kdnuggets.com/2020/08/metrics-evaluate-deep-learning-object-detectors.html
A Survey on Performance Metrics for Object-Detection Algorithms: https://www.researchgate.net/publication/343194514_A_Survey_on_Performance_Metrics_for_Object-Detection_Algorithms
Github: https://github.com/ultralytics/yolov3/issues/898
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DeText: A Deep Neural Text Understanding Framework
DeText can be applied to many tasks, including search & recommendation ranking, multi-class classification and query understanding tasks.
Github: https://github.com/linkedin/detext
Paper: https://arxiv.org/abs/2008.02460v1
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DeText can be applied to many tasks, including search & recommendation ranking, multi-class classification and query understanding tasks.
Github: https://github.com/linkedin/detext
Paper: https://arxiv.org/abs/2008.02460v1
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Question and Answer Test-Train Overlap in Open-Domain Question Answering Datasets
Github: https://github.com/facebookresearch/QA-Overlap
Paper: https://arxiv.org/abs/2008.02637
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Github: https://github.com/facebookresearch/QA-Overlap
Paper: https://arxiv.org/abs/2008.02637
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GitHub
GitHub - facebookresearch/QA-Overlap: Code to support the paper "Question and Answer Test-Train Overlap in Open-Domain Question…
Code to support the paper "Question and Answer Test-Train Overlap in Open-Domain Question Answering Datasets" - GitHub - facebookresearch/QA-Overlap: Code to support the paper &am...
Layerwise learning for Quantum Neural Networks
Training strategy that addresses vanishing gradients in quantum neural networks (QNNs).
https://blog.tensorflow.org/2020/08/layerwise-learning-for-quantum-neural-networks.html
Quirk: a drag-and-drop quantum circuit simulator with nice visualizations: https://algassert.com/quirk
Paper: https://arxiv.org/abs/2003.02989
Quantum Intuition:https://www.youtube.com/channel/UC-2knDbf4kzT3uzWo7iTJyw
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Training strategy that addresses vanishing gradients in quantum neural networks (QNNs).
https://blog.tensorflow.org/2020/08/layerwise-learning-for-quantum-neural-networks.html
Quirk: a drag-and-drop quantum circuit simulator with nice visualizations: https://algassert.com/quirk
Paper: https://arxiv.org/abs/2003.02989
Quantum Intuition:https://www.youtube.com/channel/UC-2knDbf4kzT3uzWo7iTJyw
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