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MLOps Tutorial - Building a CI/ CD Machine Learning Pipeline
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This tutorial will show you easy machine learning model deployment using Jenkins, Docker and Flask.
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☝️☝️ USE THE EXCLUSIVE COUPON CODE ABOVE TO GET 25% OFF FOR 3 MONTHS💥
💥Get $200 FREE Credits for signup. So, hurry up!💥
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In this video, we will learn:
- State of Machine Learning
- Why do ML projects & teams struggle to reach production?
- Working as a single data scientist at a startup
- ML project management
- Demo - Building a CI/ CD ML Pipeline
- Monitoring (tentative)
- Cloud best practices
Deploying AI/ML based applications is far from trivial. On top of the traditional DevOps challenges, you need to foster collaboration between multidisciplinary teams (data-scientists, data/ML engineers, software developers and DevOps), handle model and experiment versioning, data versioning, etc. Most ML/AI deployments involve significant manual work, but this is changing with the introduction of new frameworks that leverage cloud-native paradigms, Git and Kubernetes to automate the process of ML/AI-based application deployment.
#mlops #machinelearning #cicd #mlproject
💥CloudWays COUPON CODE: CLOUDGURU25
☝️☝️ USE THE EXCLUSIVE COUPON CODE ABOVE TO GET 25% OFF FOR 3 MONTHS💥
💥Get $200 FREE Credits for signup. So, hurry up!💥
╔═╦╗╔╦╗╔═╦═╦╦╦╦╗╔═╗
║╚╣║║║╚╣╚╣╔╣╔╣║╚╣═╣
╠╗║╚╝║║╠╗║╚╣║║║║║═╣
╚═╩══╩═╩═╩═╩╝╚╩═╩═╝
In this video, we will learn:
- State of Machine Learning
- Why do ML projects & teams struggle to reach production?
- Working as a single data scientist at a startup
- ML project management
- Demo - Building a CI/ CD ML Pipeline
- Monitoring (tentative)
- Cloud best practices
Deploying AI/ML based applications is far from trivial. On top of the traditional DevOps challenges, you need to foster collaboration between multidisciplinary teams (data-scientists, data/ML engineers, software developers and DevOps), handle model and experiment versioning, data versioning, etc. Most ML/AI deployments involve significant manual work, but this is changing with the introduction of new frameworks that leverage cloud-native paradigms, Git and Kubernetes to automate the process of ML/AI-based application deployment.
#mlops #machinelearning #cicd #mlproject
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