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Links and resources from our live presentations and talks

Talks

Experiment Tracking

Try our free tools for experiment tracking with this 5 minute example →

Deep Learning in the Real World

Here are the slides. If you want to join our Machine Learning community, join our forum.

If you're curious to learn more about some of the things I referenced in my talk, check out these resources:

  1. IBM over promises and under delivers with Watson for cancer detection —https://www.statnews.com/2017/09/05/watson-ibm-cancer/
  2. Deep learning models listen to machines to detect mechanical issues —https://spectrum.ieee.org/automaton/robotics/artificial-intelligence/deep-learning-ai-listens-to-machines-for-signs-of-trouble
  3. A diagram of companies in the machine learning space — http://www.shivonzilis.com/machineintelligence
  4. The Netflix Prize — https://pdfs.semanticscholar.org/31af/4b8793e93fd35e89569ccd663ae8777f0072.pdf?_ga=2.236029634.29078749.1572504512-1040137223.1572504512
  5. Autonomous car forecasts — https://ark-invest.com/research/waymo-autonomous-taxis
  6. Andrej Karpathy's ImageNet blog post — http://karpathy.github.io/2014/09/02/what-i-learned-from-competing-against-a-convnet-on-imagenet/
  7. The Stanford Dogs Dataset — http://vision.stanford.edu/aditya86/ImageNetDogs/
  8. Labradoodle or fried chicken — https://twitter.com/drjuliashaw/status/874293864814845952
  9. COMPAS recidivism scores — https://www.propublica.org/article/how-we-analyzed-the-compas-recidivism-algorithm
  10. Art to confuse facial recognition — https://cvdazzle.com/
  11. Adversarial examples on street signs — https://www.bleepingcomputer.com/news/security/you-can-trick-self-driving-cars-by-defacing-street-signs/
  12. Explainability in image classifiers — https://arxiv.org/pdf/1602.04938.pdf
  13. Explainable time series predictions — https://www.ijcai.org/proceedings/2019/0932.pdf
  14. The reproducibility crisis — https://www.wired.com/story/artificial-intelligence-confronts-reproducibility-crisis/

Natural Language Examples

  1. OpenAI GPT-2: a model for generating realistic text
  2. TalkToTransformer.com: try GPT 2
  3. GLUE Benchmark: resources for training and analyzing natural language systems
  4. SuperGLUE: updated and improved v2 of the GLUE benchmark
  5. Livox: uses NLP in an alternative communication app
  6. Practical Twitter Content Mining: medical journal article about using NLP on tweets
  7. Applications of NLP: Medium article talking about 10 interesting applications