7 Great things about #khipu.ai2019

Source: Deep Learning on Medium

7 Great things about #khipu.ai2019

This post reflects my personal opinion

During November (11th -14th) khipu.ai conference was held in Montevideo, Uruguay. It was the first conference in #latam related to AI. The idea was to recreate the Deep Learning Indaba meetings hosted in Africa. All material can be found at https://khipu.ai/program/

1. LATAM talent & networking

I think that was great about Khipu was all the people from LATAM working with related topics of ML/Deep Learning. The poster session helped me to know and talk with them. I got very impressed of the talent we have in this part of the world. Research related to bioinformatics, genomics, meteorological events, fake news, natural language processing, computer vision related to bioimage analysis. It was definitely a great experience and an amazing kickstart for AI in #latam.

2. It’s all about #community

After the event, I was able to have a talk in a city near my home. I was sharing the Khipu experience I get from getting part in the event. I also talked about some important deep learning architectures.

3. Great Technical Talks

Something great about Khipu.ai was undoubtely the speakers that attended the conference. Some inspiring talks were

  • Machine Learning Fundamentals by Luciana Ferrer
Source: @khipu.ai (Twitter account)
  • Deep Learning Fundamentals by René Vidal
  • Reinforcement Learning by Nando de Freitas
Source: My personal album of photos
  • Generative Models by Ian Goodfellow
Source: @data_datum (Twitter account)
  • Causality and Generalization by David López-Paz
Source: @khipu.ai (Twitter account)
  • Robotics and Continuous Control by Chelsea Finn
Source: @khipu.ai Twitter account)
  • Perspectives on AI by Yoshua Bengio
Source: @data_datum (Twitter account)
  • Recent advances in Deep Reinforcement Learning by Oriol Vinyals

4. Inspiring Talks

Another talks related more to applied deep learning were:

  • ML Challenges and Opportunities of Computational Behavioral Phenotyping in Developmental Health
Source: @khipu.ai (Twitter account)
  • Machine Learning and Climate Change by Claire Monteleoni
Source: @khipu.ai (Twitter account)
  • Machine Learning and Healthcare by Danielle Belgrave
Source: @khipu.ai (Twitter account)
  • Spotlights by Luciana Benotti
Source: @khipu.ai (Twitter account)

5. Khipu insights

I think there were great technical talks from basics to advanced topics in the event. I expect to write in this blog my personal reviews related to these talks soon:

  1. [Nando de Freitas] Reinforcement Learning
  2. [David López-Paz] Causality and Generalization
  3. [Luciana Ferrer] Machine Learning Fundamentals
  4. [René Vidal] Deep Learning Fundamentals

6. Tutorials

The tutorials were Python notebooks to get hands-on experience related to the following topics:

  1. Convolutional Neural Networks
  2. Optimization in Deep Learning
  3. Recurrent Neural Networks
  4. Transformer
  5. Generative Models
  6. Reinforcement Learning

All the material is here: https://github.com/data-datum/practicals-2019

7. And finally, good friends.