Top 100 alternative sites to abhaygupta.dev

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  8. Pretrained.ai — Hosted, Managed Pretrained Machine Learning Model APIs
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  10. MPercept Technology - AI Company Nepal
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  26. Learning Generative Models of 3D Structures
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  29. vtshitoyan.github.io
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  30. Vahe Tshitoyan - Machine Learning / Physics
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  32. Visual Learning and Embodied Agents in Simulation Environments
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  38. Meet Shah
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  40. Meet Shah
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  70. Machine Learning - CMU - Carnegie Mellon University | @mldcmu
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  78. Be part of it | COREMATIC
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  80. Freelance Data Scientist Thomas Wood: NLP, Deep Learning
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  82. Research Journal of Engineering Technology and Medical Sciences (RJETM)
    Research Journal of Engineering Technology and Medical Sciences RJETM is an open access journal, which aims to provide and encourage the scholars and academicians globally to share their knowledge in the fields of Engineering, Technology and its related areas.
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  83. machinethink.net
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  84. Machine, Think!
    Matthijs Hollemans is an independent machine learning consultant, app developer, and author of Machine Learning by Tutorials and Core ML Survival Guide.
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  85. phuang17.github.io
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  86. Po-Han Huang's Homepage
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  88. jiai.development - Machine Learning, AI, Automation and Cloud Technologies for SMB's
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  90. CYNET.ai - Artificial intelligence research, deep learning, neural networks, robotics
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  92. One-Stop Data Annotation & Data Labeling Service Provider
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  94. Alexander Schwing
    Our research is centered around machine learning, computer vision, deep learning, and artificial intelligence.

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  96. Isengard.no — contact info: wizard at isengard dot no
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  100. Softwareentwickler für Bildverarbeitung, Machine Learning und Fabrikautomatisierung :: MJH Maschinensehen :: Duisburg :: Ruhrgebiet
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  112. Topix - Version 3.2
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  114. Machine Learning and Computer Vision Group -- Christoph Lampert -- IST Austria
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  118. Roman V. Shapovalov
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  120. A42 Labs
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  123. humans-of.ai
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  124. Humans of AI
    Humans of AI is an online exhibition comprised of three works based on the COCO image dataset. Without legal precedent, the data by which machine learning algorithms learn to make predictions is hardly ever shown, let alone credited. By doing both, Humans of AI exposes the myth of magically intelligent machines, instead applauding the photographers that made this technical achievement possible. In fact, when showing the actual training pictures, credit is not only due but mandatory.
    Author: Philipp Schmitt

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  128. Visual Computing Group at the HTW Berlin
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  138. Homepage Prof. Petra Perner
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