As always we had a prepared agenda, however, along the way we deviated from the agenda, and things became more real. We cover the definition of Machine Learning, we also talk about some languages and tools that we have available for ML, and about the Frameworks that we can use today. AzureML, CNTK, Tensor Flow, Python, R and real experiences of ML projects. I like to learn / listen to real experiences.
Special mention to the reference of Pablo on the “you do not need to be a mathematician to work in ML”, and the explanation of Rodrigo on the reason for the popularity of Python in the ML community.
At the end of the episode we have the latest technology thanks to Sergio Mabres. I hope you enjoy, and apologize for the mistakes (if there were any).
Greetings @ Burlington
- Tools / Frameworks / Others
- Images: Smart Dog, Bad Robot
- Music Resources