MLOps Key Concepts - An Ongoing Series
Select MLOps Key Concepts
This video series live coding languages iteratively thus learning the language.
Lessons Covered Include:
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1.0 MLOps Hierarchy of Needs: DevOps, DataOps, Platform Automation and MLOps
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2.0 mlops trends
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3.0 Heavy vs Light MLOps
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4.0 MLOps Maturity Model
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5.0 What is Continuous Delivery?
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6.0 MLOps Hierarchy of Needs: DevOps, DataOps, Platform Automation and MLOps
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7.0 Key Components MLOps Landscape
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8.0 Build Cutting Edge MLOps Tools with Pre-trained LLM (Large Language Model)) for Hugging Face and OpenAI and Github Copilot
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9.0 feature store data warehouse
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10.0 data drift taleb
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11.0 ai enabled workflows
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12.0 fine tuning raw ingredients hugging face
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13.0 advantages transfer learning
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14.0 containerized ml microservices
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15.0 ai builds ai to write ai
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16.0 bespoke system core business
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17.0 simulations vs experiment tracking
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19.0 Build Pytorch Fastapi microservices deployed via AWS App Runner using AWS Cloud9 and GitHub Codespaces
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20.0 SRE Mindset for MLOps
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21.0 Teaching MLOps at scale with Github Codespaces and Copilot
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22.0 Using default Python.org download to install datascience packages with virtualenv and pip
Learning Objectives
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Learn key terminology and concepts in machine learning, data science, data operations and DevOps
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Understand foundational concepts in MLOps
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Using Hugging Face and OpenAI to build a cutting edge MLOps pipelines
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Use Github Codespaces and Copilot with Open AI Codex use AI to write AI
Additional Popular Resources