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?? Not sure which machine learning algorithm to choose? Use this handy cheat sheet ?? to find the best one for your needs!

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Seth Sekyere

Mechanical Engineer | DevOps & ML Ops Engineer | AWS Certified | Site Reliability Engineer | Six Sigma Green Belt |

5 个月

Support Vector Machine

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MARYAM ALMOUSA

Biomedical Engineer, Certified Associate in Project Management, 6 Sigma Certified Black Belt, Board Member of SSSBE & Student of Master of Science in Biomedical Engineering

5 个月

Thanks, could you please provide me the reference?

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Heitor Giatte da Costa

Control and Automation Engineering | Mechatronic Technician

5 个月
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Roxana Mihet

Professor of Finance on Tenure-Track at the University of Lausanne

5 个月

Useful tips!

Luciano Garim

Mathematician and Deep Learning Researcher

5 个月

Can you guys give us an example of neural networks interpretability as you said "Moderately easy"?

Vinod Shrivastava

Research Scholar at IIT Mandi

5 个月

Neural Network

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Jesse Yang

too busy fixing old aircrafts, no time for the AI hypes

5 个月

LR could getting both very complicated mathematically and computing intensive when multiple inputing mutations are tested/tuned. DT comes with a very poor interpretability unless it's a pruned tree.

Kartik Verma

Tata Advanced Systems Limited- Cybersecurity Project Operations- TCPSD

5 个月

i would go with random forest , but as mentioned , it depends on the dataset and your requirements.

Andres Josue Arroyo Torres

Program Safety Manager Stellantis North America - Alten México | ISO 26262 | Functional Safety

5 个月
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