A while back, I did an analysis of the family network of major characters from the A Song of Ice and Fire books and the Game of Thrones TV show. In that analysis I found out that House Stark (specifically Ned and Sansa) and House Lannister (especially Tyrion) are the most important family connections in Game of Thrones; they also connect many of the story lines and are central parts of the narrative.
These are my sketchnotes for Sam Charrington’s podcast This Week in Machine Learning and AI about Learning “Common Sense” and Physical Concepts with Roland Memisevic: Sketchnotes from TWiMLAI talk #111: Learning “Common Sense” and Physical Concepts with Roland Memisevic You can listen to the podcast here. In today’s episode, I’m joined by Roland Memisevic, co-founder, CEO, and chief scientist at Twenty Billion Neurons. Roland joined me at the RE•WORK Deep Learning Summit in Montreal to discuss the work his company is doing to train deep neural networks to understand physical actions.
Registration is now open for my 1.5-day workshop on deep learning with Keras and TensorFlow using R. It will take place on April 12th and 13th in Hamburg, Germany. You can read about one participant’s experience in my last workshop: Big Data – a buzz word you can find everywhere these days, from nerdy blogs to scientific research papers and even in the news. But how does Big Data Analysis work, exactly?
On Wednesday, April 25th 2018 I am going to talk about explainability of machine learning models at the Minds Mastering Machines conference in Cologne. The conference will be in German, though. ERKLÄRBARKEIT VON MACHINE LEARNING: WIE KÖNNEN WIR VERTRAUEN IN KOMPLEXE MODELLE SCHAFFEN? Mit Machine-Learning getroffene Entscheidungen sind inhärent schwierig – wenn nicht gar unmöglich – nachzuvollziehen. Die Komplexität einiger der besten Modelle, wie Neuronale Netzwerke, ist genau das, was sie so erfolgreich macht.
For those of you out there who speak German: I was interviewed for a tech podcast where I talked about machine learning, neural nets, why I love R and Rstudio and how I became a Data Scientist. You can download and listen to the podcast here: https://mies.me/2018/01/31/hmww17-machine-learning-mit-dr-shirin-glander/ In der aktuellen Episode gibt Dr. Shirin Glander (Twitter, Homepage) uns ein paar Einblicke in das Thema Machine Learning. Wir klären zunächst, was Machine Learning ist und welche Möglichkeiten es bietet bevor wir etwas mehr in die Tiefe gehen.
I am happy to announce that on Tuesday, April 24th 2018 Uwe Friedrichsen and I will give a talk about Deep Learning - a Primer at the JAX conference in Mainz, Germany. Deep Learning is one of the “hot” topics in the AI area – a lot of hype, a lot of inflated expectation, but also quite some impressive success stories. As some AI experts already predict that Deep Learning will become “Software 2.
These are my sketchnotes for Sam Charrington’s podcast This Week in Machine Learning and AI about Neuroevolution: Evolving Novel Neural Network Architectures with Kenneth Stanley: Sketchnotes from TWiMLAI talk #94: Neuroevolution: Evolving Novel Neural Network Architectures with Kenneth Stanley You can listen to the podcast here. Kenneth studied under TWiML Talk #47 guest Risto Miikkulainen at UT Austin, and joined Uber AI Labs after Geometric Intelligence , the company he co-founded with Gary Marcus and others, was acquired in late 2016.
- OLDER POSTS
- page 1 of 4