Background: I’m a Computer Vision Engineer working for some time in the industry now (3-4 years). HTM’s have always piqued my interest ever since I stumbled across the youtube video by Taylor.
Every time I go through a topic I get lost in the plethora of resources available. I enjoyed the topics of sparse representations and predictive processing. And reading about predictive processing linked me to neural generative coding framework. Somehow I’ve ended up back again here. Is there a structured way of learning things about these topics (sparse representations and predictive processing etc) without getting lost??
I’m particularly interested in the research and implementation side of things. Any help would be appreciated.
Thanks.
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My strong guess is that this is NOT a non-dualistic approach …
Professor REZA SANAYE
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Hey @ajaynaidu, welcome!
I know you mentioned ‘the YouTube video’ by Matt Taylor, but have you seen his whole series called HTM School? This is the first thing I’d personally recommend, since the videos are brief and engaging with great visuals. Matt was a 1-man army on these and he is deeply missed professional as well as personally.
On the implementation side I’d recommend looking at NAB (Numenta Anomaly Benchmark), where HTM was evaluated alongside a few other time series anomaly detectors on a battery of real & artificial data sets with labeled anomalies.
Also related to implementation I’ve actually written a wrapper module around htm.core, allowing for quick prototyping for time series anomaly detection. If you’re looking to do that kind of application let me know and I can give you access.
Hope this helps get the ball rolling and again welcome to the community 
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Somewhat dated but still useful:
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Thanks @Bitking will take a look at it
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I just read up about it. This was disheartening to read.
Let me take a look at the NAB. Will drop a text regarding the wrapper once I’m done with the reading about BAMI and NAB.
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