What's the Life Cycle of a Data Scientist? • E. Sirazitdinova, P. Daniel & N. Stålung • GOTO 2021

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This interview was recorded at GOTO Copenhagen 2021 for GOTO Unscripted. #GOTOcon #GOTOunscripted #GOTOcph

Read the full transcription of this interview here:

Ekaterina Sirazitdinova - Data Scientist for Computer Vision, Video Analytics & Deep Learning at NVIDIA
Prayson Daniel - Principal Data Scientist at NTT DATA
Nicholai Stålung - Lead Data Scientist at Trifork

Data science is so much more than collecting, sorting and analyzing data. What does it take to be a data scientist and how does a day in the life of a data scientist look like? Ekaterina Sirazitdinova, Prayson Daniel and Nicholai Stålung will give you an insight into this and more.

00:00 Intro
01:48 Interpretability and expandability
06:43 Testing models outside of the lab
09:55 The best model is no model
16:28 Simplify the workflow for data scientists & perfect automation
21:15 Is coding part of the future data sciences?
26:43 Outro

Phil Winder • Reinforcement Learning • https://amzn.to/3t1S1VZ
Kelleher & Tierney • Data Science (The MIT Press Essential Knowledge series) • https://amzn.to/3AQmIRg
Lakshmanan, Robinson & Munn • Machine Learning Design Patterns • https://amzn.to/2ZD7t0x
Lakshmanan, Görner & Gillard • Practical Machine Learning for Computer Vision • https://amzn.to/3m9HNjP
Aurélien Géron • Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow • https://amzn.to/2XZaQy8

#DataScience #ML #AI #MachineLearning #ArtificialIntelligence #Programming #EkaterinaSirazitdinova #KatjaSirazitdinova #PraysonDaniel #NicholaiStalung #Trifork #NTTDATA #NVIDIA #MixedPosition #Interpretability #Expandability #TensorFlow #PyTorch #TAO #TAOToolkit #DeepLearning #HuggingFace

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