How to Learn from Little Data - Intro to Deep Learning #17

One-shot learning! In this last weekly video of the course, i'll explain how memory augmented neural networks can help achieve one-shot classification for a small labeled image dataset. We'll also go over the architecture of it's inspiration (the neural turing machine). Code for this video (with challenge): https://github.com/llSourcell/How-to-Learn-from-Little-Data Please subscribe! And like. And comment. That's what keeps me going. More learning resources: https://www.youtube.com/watch?v=CzQSQ_0Z-QU https://arxiv.org/abs/1605.06065 https://futuristech.info/posts/differential-neural-computer-from-deepmind-and-more-advances-in-backward-propagation https://thenewstack.io/googles-deepmind-ai-now-capable-deep-neural-reasoning/ Join us in the Wizards Slack Channel: http://wizards.herokuapp.com/ And please support me on Patreon: https://www.patreon.com/user?u=3191693 Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/