Catch up with the fast moving field of data science. Even for us it has been difficult to stay up to date with the latest news and developments in the industry. We are putting together some of the top sources such as MIT, NVIDIA, ARXIV and others. These articles are aggregated from well trusted sources in the community. We will continue to add more sources and refine the type of articles showcased here over time.
Data Science
The recent developments in the field of data science and AI. Sources: Explosion.ai, Rasa, fast.ai, MIT, Berkley, Uber, IBM and Google AI Blog and other trusted sources.
- RLDS: An Ecosystem to Generate, Share, and Use Datasets in Reinforcement Learningby Google AI on December 1, 2021 at 7:08 pm
Posted by Sabela Ramos, Software Engineer and Léonard Hussenot, Student Researcher, Google Research, Brain Team Most […]
- MURAL: Multimodal, Multi-task Retrieval Across Languagesby Google AI on November 30, 2021 at 9:03 pm
Posted by Aashi Jain, AI Resident and Yinfei Yang, Staff Research Scientist, Google Research For many concepts, […]
- Artificial intelligence that understands object relationshipsby Adam Zewe | MIT News Office on November 29, 2021 at 5:00 am
A new machine-learning model could enable robots to understand interactions in the world in the way humans do.
- Neural edit-tree lemmatization for spaCyon November 24, 2021 at 12:00 am
We are happy to introduce a new, experimental, machine learning-based lemmatizer that posts accuracies above 95% for […]
- Doing Data Science for Social Good, Responsiblyby fast.ai on November 23, 2021 at 12:00 am
The phrase “data science for social good” is a broad umbrella, ambiguously defined. As many others have pointed […]
News
- Machine learning in Earth and environmental science requires education and research policy reforms – Nature.comon December 2, 2021 at 4:05 pm
Machine learning in Earth and environmental science requires education and research policy reforms Nature.com
- Better Machine Learning Demands Better Data Labeling – Datanamion December 2, 2021 at 3:41 pm
Better Machine Learning Demands Better Data Labeling Datanami
- Better Machine Learning Demands Better Data Labeling – Datanamion December 2, 2021 at 3:41 pm
Better Machine Learning Demands Better Data Labeling Datanami
- Real2sim2real: A self-supervised learning technique applied to planar robot casting – Tech Xploreon December 2, 2021 at 2:44 pm
Real2sim2real: A self-supervised learning technique applied to planar robot casting Tech Xplore
- Katharine Jarmul on Machine Learning at the Edge – InfoQ.comon December 2, 2021 at 2:00 pm
Katharine Jarmul on Machine Learning at the Edge InfoQ.com
White Papers
Latest research and developments in the field of machine learning and deep learning. Sources: ARXIV, Papers with Code and others
- Leveraging Intrinsic Gradient Information for Machine Learning Model Training. (arXiv:2112.00094v1 [cs.LG])
Designing models that produce accurate predictions is the fundamental objective of machine learning. This work presents […]
- A Comprehensive Study on Various Statistical Techniques for Prediction of Movie Success. (arXiv:2112.00395v1 [cs.LG])
The film industry is one of the most popular entertainment industries and one of the biggest markets for business. […]
- A benchmark with decomposed distribution shifts for 360 monocular depth estimation. (arXiv:2112.00432v1 [cs.CV])
In this work we contribute a distribution shift benchmark for a computer vision task; monocular depth estimation. Our […]
- SaDe: Learning Models that Provably Satisfy Domain Constraints. (arXiv:2112.00552v1 [cs.LG])
With increasing real world applications of machine learning, models are often required to comply with certain domain […]
- Multi-Agent Transfer Learning in Reinforcement Learning-Based Ride-Sharing Systems. (arXiv:2112.00424v1 [cs.LG])
Reinforcement learning (RL) has been used in a range of simulated real-world tasks, e.g., sensor coordination, traffic […]