Interested in Data Science, Analytics and Artificial Intelligence?
This podcast, Symbolic Connection will help you to understand all aspects of Data Science and Artificial Intelligence.
Run by practitioners with a combined experience of more than 10 years+, they share what they have learned.
The topics will vary from data, algorithms, implementation, business applications, and more. All from an applied perspective.
Find out what’s developing in the field. Give it a listen 👇
Feedback: https://forms.gle/fnnJ6QGrjj4Yv74z5
Contact: symbolic.connection@gmail.com
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Interested in Data Science, Analytics and Artificial Intelligence?
This podcast, Symbolic Connection will help you to understand all aspects of Data Science and Artificial Intelligence.
Run by practitioners with a combined experience of more than 10 years+, they share what they have learned.
The topics will vary from data, algorithms, implementation, business applications, and more. All from an applied perspective.
Find out what’s developing in the field. Give it a listen 👇
Feedback: https://forms.gle/fnnJ6QGrjj4Yv74z5
Contact: symbolic.connection@gmail.com
So what is MLOps? This is a topic we covered in this episode. We discuss the different aspects of MLOps, for instance, data, business requirements, and also measuring the performance metrics. We discuss also data quality and feature engineering and its impact on the ML pipelines as well. We also do a short introduction on the different tools used in MLOps, such as Containers, Kubernetes, and Airflow. And let us throw in one more technical term...data versioning. Give us a listen to understand what that is!
Learning Resources:
1. What is MLOps (https://whatis.techtarget.com/definition/machine-learning-operations-MLOps)
2. Getting started with MLOps (https://ml-ops.org/)
3. MLOps Fundamentals with GCP (https://www.coursera.org/learn/mlops-fundamentals)
4. Difference between Data Scientist and MLOps Engineer (https://towardsdatascience.com/data-scientist-vs-machine-learning-ops-engineer-heres-the-difference-ad976936e651)
5. Learn Docker (https://www.youtube.com/watch?v=fqMOX6JJhGo)
6. Learn Kubernetes (https://kubernetes.io/docs/tutorials/kubernetes-basics/)
8. https://www.deeplearning.ai/program/machine-learning-engineering-for-production-mlops/
Symbolic Connection
Interested in Data Science, Analytics and Artificial Intelligence?
This podcast, Symbolic Connection will help you to understand all aspects of Data Science and Artificial Intelligence.
Run by practitioners with a combined experience of more than 10 years+, they share what they have learned.
The topics will vary from data, algorithms, implementation, business applications, and more. All from an applied perspective.
Find out what’s developing in the field. Give it a listen 👇
Feedback: https://forms.gle/fnnJ6QGrjj4Yv74z5
Contact: symbolic.connection@gmail.com
