Using neural networks to explore natural language.
A demonstration of basic reinforcement learning problems.
Explore a highly effective deep learning approach to sentiment analysis using TensorFlow and LSTM networks.
Learn how to tokenize, breaking a sentence down into its words and punctuation, using NLTK and spaCy.
How to build and train an image caption generator using a TensorFlow notebook.
Learn how deep learning has accelerated the realization of driverless vehicles and what that means for the future.
Learn how you can open up non-text content to search with deep learning.
Learn how Facebook and other trailblazers use AI technologies to recognize human features.
The adventures in deep learning and cheap hardware continue!
Mike Barlow examines the growth of sophisticated cloud-based AI and machine learning services for a growing market of developers and users in business and academia.
An informative, visual, and interactive MNIST tutorial.
A define-by-run approach allows for flexibility and simplicity when building deep learning networks.
Running your image classifier in your own iOS application.
Take deep learning mobile.
Adventures in deep learning, cheap hardware, and object recognition.
Building a fast, accurate image classifier on the cheap.
Building and training your first TensorFlow graph from the ground up.
Pete Warden’s instructions on building a deep learning classifier looked so simple, I had to try it myself.
How to build your own image classifier with no coding.
This post is an introduction to a popular dimensionality reduction algorithm: t-distributed stochastic neighbor embedding (t-SNE).
Adam Marcus explains how to effectively benefit from crowd workers to solve your most challenging tasks. He uses examples from the wild and from his work at GoDaddy.
In this webcast Matthew Kirk will detect sentiment in tweets using the Support Vector Machines algorithm.
Step-by-step instruction on training your own neural network.