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Jithin Pradeep
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Instinct and Intuition doesn't Lie as they are mine.
Instinct and Intuition doesn't Lie as they are mine.

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Does someone know a better way to embed iPython or jupyter notebook to WordPress? With the approach I used there is vertical scroll bar associated with embedded notebook, which limit the display. Is there a method to overcome this?
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Interpreting Deep Neural Networks using Cognitive Psychology

Deep neural networks have learnt to do an amazing array of tasks - from recognising and reasoning about objects in images to playing Atari and Go at super-human levels. As these tasks and network architectures become more complex, the solutions that neural networks learn become more difficult to understand. This is known as the ‘black-box’ problem, and it is becoming increasingly important as neural networks are used in more and more real world applications. At DeepMind, we are working to expand the toolkit for understanding and interpreting these systems. In our latest paper, recently accepted at ICML, we proposed a new approach to this problem that employs methods from cognitive psychology to understand deep neural networks. Cognitive psychology measures behaviour to infer mechanisms of cognition, and contains a vast literature detailing such mechanisms, along with experiments for verifying them. As our neural networks approach human level performance on specific tasks, methods from cognitive psychology are becoming increasingly relevant to the black-box problem.
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Wiring of the Human Brain

Magnetic resonance imaging (MRI) has revolutionized medicine and biomedical research since its inception in the early 1970's. The technique relies upon strong magnetic fields and radio waves to non-invasively generate three-dimensional anatomical imagery without requiring the use of ionizing radiation (e.g. x-rays).

This detailed scan of the brain generated by Cardiff University's Brain Research Imaging Centre uses a different MRI technique called Diffusion Tensor Imaging (DTI), which maps the flow of water inside the brain. DTI measures a parameter called anisotropy, which describes the directionality of water molecule diffusion within neuronal structures. By performing a voxel-by-voxel analysis, researchers can construct three-dimensional representations of the axonal tracts in the brain.

Source: http://www.bbc.com/news/health-40488545 (BBC)

#ScienceGIF #Science #GIF #Brain #Wiring #MRI #DTI #Magnetic #Resonance #Imaging #Medical #Biomedical #Technology #BBC #Axon #Neuron #Tract #Tractography #Flow #Cardiff #University #Research #Scientist #Diffusion #Tensor
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More data means better machine learning
Ofcourse the title is no news, still surprising there is no slowdown in improving machine learning with adding more data.
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How AI detectives are cracking open the black box of deep learning

Each month, it seems, deep neural networks, or deep learning, as the field is also called, spread to another scientific discipline. They can predict the best way to synthesize organic molecules. They can detect genes related to autism risk. They are even changing how science itself is conducted. The AIs often succeed in what they do. But they have left scientists, whose very enterprise is founded on explanation, with a nagging question: Why, model, why? That interpretability problem, as it’s known, is galvanizing a new generation of researchers in both industry and academia. Just as the microscope revealed the cell, these researchers are crafting tools that will allow insight into the how neural networks make decisions. Some tools probe the AI without penetrating it; some are alternative algorithms that can compete with neural nets, but with more transparency; and some use still more deep learning to get inside the black box. Taken together, they add up to a new discipline. Yosinski calls it “AI neuroscience.”
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1964 Ford Canada. Interesred in old ford cars? Priceless article for such viewers have a look. Re-blogged : https://themarquisblogger.wordpress.com/2016/12/15/1964-ford-canada/  
1964 Ford Canada
1964 Ford Canada
jithinjp.in
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An algorithm learns sentiment
An interesting unintended effect of training this model.
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