Overview
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Explore the world of neural networks through an interactive browser-based experience in this code::dive 2018 conference talk. Delve into the rapid progress of deep learning and artificial neural networks, from image recognition to AlphaGo Zero's self-learning capabilities. Learn about the accessibility of deep learning using Python libraries like Keras and PyTorch, and discover the potential of TensorFlow.js for browser-based applications. Examine various use cases, including research paper demos, artistic projects, and privacy-focused applications like LSTM for code autocompletion. Journey through diverse topics such as quantum games, science-based games, medical imaging applications, satellite image processing, and machine learning model visualizations. Gain insights into text generation, interactive machine learning, and the open-source community's role in advancing these technologies.
Syllabus
Intro
Quantum Game with Photons
Science-based games
What do they see?
Skin cancer detection
X-ray for detecting broken bones
Satellite images to maps
Image segmentation
functional magnetic resonance - picture in your mind
Machine learning models
Spreadsheet-based deep learning
Decision trees, visually
Matrix factorizaton
Convolutions
king - man + woman = queen; but why?
Some accessible by API
Use cases
Text generation, char by char
How to draw an owl?
Interactive ML
Open-source community
Thank you! Questions?
Taught by
code::dive conference