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  • www.telekonix.com
Understanding Supervised Learning Through Code In this third part of our series on supervised learning, we focus on the application of supervised learning techniques using Python. Supervised learning, a cornerstone of machine learning, involves.......
Relevance: 22.648129
  • sslad2021.github.io
Deviating from the traditional path of supervised learning, recent research efforts have been directed towards self-supervised learning, large-scale pretraining, weakly supervised learning and incremental/continual learning. To promote this..
Relevance: 20.826263
  • www.floatml.com
  • 1
I summarize recent papers in deep learning. My selection of papers is biased towards alternatives to supervised learning such as: unsupervised learning, self-supervised learning, active learning etc. However, I occasionally pick interesting papers..
Relevance: 19.773354
  • eugenelet.github.io
  • 1
4th year PhD student in Electronics Engineering at National Chiao Tung University, advised by Dr. Chen-Yi Lee. Focusing in machine learning approaches suited for self-supervised or autonomous learning. Works mainly on causal learning, meta-learning,..
Relevance: 18.882387
  • airis-ai.com
  • 1
AIRIS is an Artificial General Intelligence (AGI) project based on a new type of reinforcement based symbolic learning. It is capable of supervised, unsupervised, one-shot, and online learning...
Relevance: 18.430916
  • sslad2022.github.io
  • 5
Self-supervised Learning for Next-generation Industry-level Autonomous Driving refers to a variety of studies that attempt to refresh the solutions for challenging real-world perception tasks by learning from unlabeled or semi-supervised large-scale..
Relevance: 18.374125
  • geography-aware-ssl.github.io
Contrastive learning methods have significantly narrowed the gap between supervised and unsupervised learning on computer vision tasks. In this paper, we explore their application to geo-located datasets, e.g. remote sensing, where unlabeled data is..
Relevance: 18.095201
  • salin247inc.com
  • 2
  • 2
- Bachelor's or Master's degree in Data Science, Machine Learning, or a related field... - Strong background in machine learning, including supervised and unsupervised learning, deep learning, and reinforcement learning... A Midwest, agricultural..
Relevance: 18.061373
  • vissl.ai
Reproducible reference implementation of SOTA self-supervision approaches (like SimCLR, MoCo, PIRL, SwAV etc) and their components that can be reused. Also supports supervised trainings... A library for state-of-the-art self-supervised learning from..
Relevance: 17.522602
  • ruohanw.github.io
I'm a research scientist at Institute for Infocomm Research, A*STAR. Previously, I was a postdoctoral researcher at UCL's Intelligent Systems Group, supervised by Prof. Massimiliano Pontil. I completed my Ph.D. in machine learning at Imperial..
Relevance: 17.425905
  • numl.net
The purpose of machine learning is to find (and exploit) patterns in data. Traditionally developers, when faced with a problem, develop an algorithm and write code. Certain classes of problems, however, do not lend themselves to this approach. With..
Relevance: 17.147003
  • fortuitousdata.github.io
Current successful approaches to natural language processing (NLP) are for the most part based on supervised learning. In turn, supervised learning critically depends on the availability of annotated data. Such data is generally not plentiful, as it..
Relevance: 17.044245
  • wangwllu.com
  • 1
I am a researcher at JD.com. Previously, I received my Ph.D. degree and B.Sc. degree at Nanjing University in 2014 and 2020 respectively, supervised by Prof. Zhi-Hua Zhou and Prof. Yuan Jiang. My research focuses on machine learning, especially..
Relevance: 16.729153
  • juniorcodingclub.com
  • 1
Let your child become a member of the Junior Coding Club and thrive with digital skills. Educody developed a supervised education service..... Learn and team up from anywhere, anytime with the Coding Club Membership, managed by Educody.....
Relevance: 16.438183
  • www.neeharperi.com
  • 1
I am a second year PhD student at the Robotics Institute. I'm interested in developing algorithms that can generalize (few-shot and zero-shot learning) with less supervision (self-supervised learning) and (long-tail) data. My work uses computer..
Relevance: 16.391111
  • davidpaulowen.com
  • 1
Welcome! I'm a machine learning researcher and software engineer with expertise in computer vision, deep learning, Bayesian statistics and numerical programming. I currently work at Digital Surgery @ Medtronic, where I study machine learning methods..
Relevance: 16.244146
  • www.aispace.org
  • 3
Poole, D., and Mackworth, A. 2001. CIspace: Tools for Learning Computational Intelligence. In Proceedings of the IJCAI Workshop on Effective Interactive AI Resources. BibTeX... Amershi, S., and Conati, C. 2007. Unsupervised and supervised machine..
Relevance: 16.18619
  • blasern.github.io
I am an associate professor in the Machine Learning group and the Center for Data Science at the Department of Informatics, University of Bergen. My research interests are focused on topological methods in statistics and machine learning. Topological..
Relevance: 16.15658
  • www.debadityashome.com
  • 2
I'm a graduate student pursuing MASc in AI (research) at Queen's University. My research interests include Generative models, Self-supervised learning, Multi-modality, and learning universal representations of time-series. I'm an author of 10+..
Relevance: 16.13537
  • www.dgriffiths.uk
  • 1
Hi! I'm an Applied Research Scientist at Apple. I work primarily in the field of 3D scene understanding, using deep learning methods. My previous research involved adressing the scarcity of manually labelled 3D data through alternative learning..
Relevance: 16.127419
  • hsg-aiml.github.io
This website presents research results of the Artificial Intelligence and Machine Learning [AI:ML] lab at the University of St. Gallen... Our deep neural networks research focuses on representation learning through supervised and unsupervised..
Relevance: 15.969313
  • gaussianprocess.com
  • 5
  • 5
Gaussian Process is powerful non-parametric machine learning technique for constructing comprehensive probabilistic models of real world problems. They can be applied to geostatistics, supervised, unsupervised, reinforcement learning, principal..
Relevance: 15.932124
  • www.gaussianprocess.com
  • 5
  • 5
Gaussian Process is powerful non-parametric machine learning technique for constructing comprehensive probabilistic models of real world problems. They can be applied to geostatistics, supervised, unsupervised, reinforcement learning, principal..
Relevance: 15.904175
  • www.tantrasi.com
This year-long training is open to those who desire a thorough, philosophically grounded, well supervised Sacred Intimate training. The training will primarily focus on learning and applying Tantric principles and practices, and somatic skills for..
Relevance: 15.825597
  • cloudsen12.github.io
CloudSEN12 is designed to support both weakly and self-/semi-supervised learning strategies by including three distinct forms of hand-crafted labeling data: high-quality, scribble and no-annotation...
Relevance: 15.818585
  • www.versolearning.com
  • 1
Verso's unique Instant Check-in uses supervised machine learning to reveal student understanding and wellbeing during the lesson... Running Verso Check-ins consistently in class improves student understanding of the learning focus by 51%... Verso..
Relevance: 15.816532
  • www.sun-xr-project.eu
  • 3
The aim of the proposed rehabilitation scenario is to motivate the patient to exercise efficiently by providing feedback in relation to performance, while the physiotherapy exercises are performed in any setting, e.g. clinical, at home, indoors,..
Relevance: 15.592651
  • tmbdev.github.io
I'm a researcher at NVIDIA, working on petascale deep learning, self-supervised training, text recognition, causality and sequence modeling, and the connection between statistics and deep learnining... Prior to NVIDIA, I worked at Google Brain,..
Relevance: 15.519625
  • www.boltzmann.be
  • 1
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Our team includes seasoned cross-disciplinary experts in (un)supervised machine learning, deep learning, complex modelling, and state-of-the-art Bayesian approaches. Not to mention that Boltzmann accommodates specialists in untangling network..
Relevance: 15.513643
  • beyondrl.org
  • 1
BeyondRL is an initiative started to bridge the gap between teaching and cutting-edge RL. We believe developments in this field are so promising that it is worthwile to discuss selected topics every now and then. Website and organisation thanks to..
Relevance: 15.418118