In this episode, our guest was Balázs Kégl who is head of AI Research at Huawei Paris. We were talking about machine learning projects from the organizational point of view. We talked about the relationship between technical and non-technical people, and why are there so many POC projects why only a few of them is productionised? So, if you are a data scientist and you cannot convince your manager or your client to create a project, you should definitely listen to this episode. Moreover, we talked about some technical stuff at the end.
Connect Balazs at Linkedin:
https://www.linkedin.com/in/balazskegl/
---General Info---
About the host: Miklos Toth is a Machine Learning enthusiast who is also teaching Machine Learning and Deep Learning at international companies, working on various ML projects as an engineer.
About the co-host: Levente Szabados is a Deep tech leader, consultant, and manager with a special interest in artificial intelligence, cognitive sciences, data science, and deep learning. He is teaching various ML courses at the Frankfurt School of Finance and Management.
About the podcast: The podcast was created to serve the technical community with details of ML algorithms, use-cases. The episodes are recorded in Budapest, Hungary, Europe.
Website of the podcast: http://machinelearningcafe.org/
Host's LinkedIn: https://www.linkedin.com/in/miklostoth/
Co-Host LinkedIn: https://www.linkedin.com/in/levente-szabados-76334728/
Write an email to the host: miklos@machinelearningcafe.org
Equipment: On the host's side the show is recorded with Rode Procaster and with Roland Quad-Capture audio interface.
---Copyright Info---
Music is from https://filmmusic.io, intro first part is by Miklos Toth and some free garage band loops. :) intro second part: "Aces High" by Kevin MacLeod, outro "Acid Trumpet" by Kevin MacLeod (https://incompetech.com), License: CC BY (http://creativecommons.org/licenses/by/4.0/)
Alternative Learning Methods 01 with Dmitry Krotov - 015
"Monkeys with laptops" - the (hi)story of applying AI in real life with Denis Rothman - 014
Conversational AI at Rasa with Vladimir Vlasov - 013
What's real and what's hype? - Decades of ML with Eugene Dubossarsky - 012
Extra: Machine Learning at John Deere with Marco Lemessi - 011
The World’s first Quadruple Kaggle Grandmaster - Abhishek Thakur - 010
Everything is just a wicked graph with Benedek Rozemberczki - 009
Ratings and Marketing Attribution at Foursquare with Max Sklar - 008
MISH Activation Function with Diganta Misra - 007
Finding the label errors with Cleanlab with Curtis Northcutt - 006
A New Deep Learning Optimizer called Ranger with Less Wright - 005
Cutting-Edge Gradient Descent Variants with Levente Szabados - 004
Tree-based methods for procurement & are expert systems alive? with Renee Ahel - 003
Can we predict the accuracy of a Neural Network? Yes, with the WeightWatcher tool by Charles Martin, Ph.D. - 002
Progressively Growing GANs & Style GANs with Alexandr Honchar - 001
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