6 julho 2017
C F
A L Link
clique para mostrarTem dois cheat-sheets legais para ajudar a escolher o algoritmo certo para cada problema: http://scikit-learn.org/stable/tutorial/machine_learning_map/index.html https://docs.microsoft.com/pt-br/azure/machine-learning/machine-learning-algorithm-cheat-sheet
Data science is much more than machine learning though. Data, in data science, may or may not come from a machine or mechanical process (survey data could be manually collected, clinical trials involve a specific type of small data) and it might have nothing to do with learning as I have just discussed. But the main difference is the fact that data science covers the whole spectrum of data processing, not just the algorithmic or statistical aspects. In particular, data science also covers
Link
clique para mostrar
clique para mostrar
https://www.quora.com/What-is-the-difference-between-a-machine-learning-engineer-and-a-data-scientist-at-Quora
Both machine learning engineers and data scientists are involved in machine learning at Quora. In the context of machine learning, the main summary of the differences is the following:
Machine learning engineers build, implement, and maintain production machine learning systems.
Data scientists conduct research to generate ideas about machine learning projects, and perform analysis to understand the metrics impact of machine learning systems.
O trabalho de um data scientist é criar um modelo com base em algum conjunto de dados, tentando resolver algum problema.
Feito isso, o ML engineer pega esse modelo e torna ele um sistema "em produção".
Considerando que estamos no Brasil e as coisas funcionam na base da gambiarra, muitas vezes uma empresa, quando contrata um data scientist, dá esses 2 trabalhos aí 👆pra ele fazer. Existem exceções, claro, mas não conheço muitas.
C P D
P C