<commit_before>---
author: <NAME>
brief: "Sitting at the intersection of neuroscience and computer science, we encounter interest in our work from a variety of people.  For the scientific and academic community, we have a growing list of peer-reviewed papers. The machine learning and data science enthusiasts can dive into our open source code and experiment with it firsthand. But what about those of us with no exposure to neuroscience"
date: 2017/03/03
hideImage: false
image: ../images/ep11.png
org: Director of Marketing
tags: numenta hierarchical temporal memory htm school
title: "HTM School teaches Numenta’s theory of intelligence"
type: post
---

Sitting at the intersection of neuroscience and computer science, we
encounter interest in our work from a variety of people. For the
scientific and academic community, we have a growing list of
peer-reviewed [papers](http://www.numenta.com/papers). The machine
learning and data science enthusiasts can dive into our open source code
and experiment with it firsthand. But what about those of us with no
exposure to neuroscience – those of us who are neither mathematicians
nor engineers, those of us who’ve never taken a computer science course?
Where do we go when we want to understand the fundamental concepts of
HTM Theory? We go to [HTM School](http://numenta.org/htm-school/).

HTM School was created nearly a year ago, by Numenta’s Open Source Flag
Bearer, [Matt
Taylor](https://discourse.numenta.org/users/rhyolight/activity), in an
attempt to make HTM Theory more accessible by breaking it down into
bite-sized, 15-20 minute episodes filled with stories, examples and
illustrations. The series is designed to be viewed in order, starting
with a high level overview in Episode zero. From there, Matt lays out
core components of the theory, one episode at a time: from how we
represent information to how we learn spatial patterns.

The series has attracted a nice following, with more than 35,000 total
views and a healthy amount of Q&A that takes place in the comments<commit_msg>Update htm-school.md<commit_after>---
author: <NAME>
brief: "Sitting at the intersection of neuroscience and computer science, we encounter interest in our work from a variety of people.  For the scientific and academic community, we have a growing list of peer-reviewed papers. The machine learning and data science enthusiasts can dive into our open source code and experiment with it firsthand. But what about those of us with no exposure to neuroscience"
date: 2017/03/03
hideImage: false
image: ../images/ep11.png
org: Director of Marketing
tags: numenta hierarchical temporal memory htm school
title: "HTM School Teaches Numenta’s Theoretical Framework for Biological and Machine Intelligence"
type: post
---

Sitting at the intersection of neuroscience and computer science, we
encounter interest in our work from a variety of people. For the
scientific and academic community, we have a growing list of
peer-reviewed [papers](http://www.numenta.com/papers). The machine
learning and data science enthusiasts can dive into our open source code
and experiment with it firsthand. But what about those of us with no
exposure to neuroscience – those of us who are neither mathematicians
nor engineers, those of us who’ve never taken a computer science course?
Where do we go when we want to understand the fundamental concepts of
HTM Theory? We go to [HTM School](http://numenta.org/htm-school/).

HTM School was created nearly a year ago, by Numenta’s Open Source Flag
Bearer, [Matt
Taylor](https://discourse.numenta.org/users/rhyolight/activity), in an
attempt to make HTM Theory more accessible by breaking it down into
bite-sized, 15-20 minute episodes filled with stories, examples and
illustrations. The series is designed to be viewed in order, starting
with a high level overview in Episode zero. From there, Matt lays out
core components of the theory, one episode at a time: from how we
represent information to how we learn spatial patterns.

The series has attracted a nice following, with more than 35,000 total
views and a healthy amount of Q&A that takes place in the comments
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