Ultimate MLOps Full Course in One Video ๐ฅ
๐ Welcome to the Ultimate MLOps Full Course in One Video (12 Hours)
Master Machine Learning Operations (MLOps) with this comprehensive 12-hour crash course. Designed for data scientists, ML engineers, DevOps professionals, and AI enthusiasts, this course covers everything from model building to deployment using modern MLOps tools and practices.
๐ What You'll Learn:
๐๐ปIntroduction to MLOps and its importance
๐๐ปEnd-to-End ML pipeline setup
๐๐ปML Pipeline Management using DVC
๐๐ปCI/CD for ML with GitHub Actions, Circle CI & Jenkins
๐๐ปContainerization using Docker
๐๐ปOrchestration with Kubernetes
๐๐ปModel tracking & registration with MLflow
๐๐ปModel deployment using FastAPI, Flask, and more
๐๐ปMonitoring and logging
๐๐ปAmazon Sagemekaer
๐๐ปCloud deployment tips (AWS/GCP)
๐ Resources:
๐ Code Repository: https://github.com/entbappy/Ul....timate-MLOps-Full-Co
๐๐ปTable of contents:
00:00:00 - Introduction & Overview
00:52:08 - Understand MLOPs with Real World Analogy
00:41:07 - Introduction to MLOps & Importance
01:14:11 - Why Linux for MLOps
01:25:45 - Setting Up Linux with AWS EC2
01:31:55 - Required Linux Commands for MLOps
01:54:09 - Getting Started With Git And GitHub
02:08:22 - Local and Remote Repository Setup
02:13:16 - How to do code management using Git
02:22:01 - Git Branch Management
02:25:53 - Introduction to DVC
02:37:31 - Build & Track ML Pipelines with DVC
03:09:31 - Fundamentals of Cloud for MLOps
03:26:39 - Introduction to MLFlow and Experiment Tracking
03:42:34 - MLFlow Experiment Tracking with Dagshub
04:05:17 - Docker Introduction
04:25:30 - Docker Installation
04:30:13 - Docker Practical Demo
04:37:42 - Creating our custom images with Docker
04:52:33 - End-to-End Real ML Project Implementation with MLOPs
07:20:16 - CICD: Continuous integration and continuous delivery/deployment
07:25:47 - CICD Deployment with GitHub Actions
07:42:46 - CICD Deployment with Jenkins
09:12:18 - CICD Deployment with Circle CI
10:18:09 - Kubernetes
10:46:14 - ML Project using AWS Sagemaker
11:08:48 - Grafana for Monitoring
#MLOps #MLOpsCourse #MachineLearning #EndToEndML #MLProject #CI_CD #Docker #Kubernetes #MLflow #DataScience #MLOpsTools #DevOps #AI #ModelDeployment #FullCourse
Check out my other playlists:
โบ MLOps Production Ready Machine Learning Project: https://youtube.com/playlist?list=PLkz_y24mlSJZvJOj1UXiJPVRQrNFdNEXX&si=yxL3EpwDcOslx3du
โบ End To End Data Science Projects Implementation: https://youtube.com/playlist?list=PLkz_y24mlSJaGcOXgJSuMM62sFha4fank&si=L0O96gFeduHCEVdi
โบ MLflow For Data Science | MLOps: https://youtube.com/playlist?list=PLkz_y24mlSJZrqiZ4_cLUiP0CBN5wFmTb&si=mOOoyy6gcNmG3IqS
โบ The Complete Self Driving Car Course: https://youtube.com/playlist?list=PLkz_y24mlSJawbZz-fJrrxZi0QNmJ5aP6&si=iC2PZhLG5Q5J3tF6
โบ Object Detection Using YOLO v6: https://youtube.com/playlist?l....ist=PLkz_y24mlSJY3H0
โบ Object Detection Using YOLO v7: https://youtube.com/playlist?l....ist=PLkz_y24mlSJagh6
โบ Sign Language Detection Using YOLO v5: https://youtube.com/playlist?l....ist=PLkz_y24mlSJYWpw
โบONNX (Open Neural Network Exchange): https://youtube.com/playlist?l....ist=PLkz_y24mlSJZJx9
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This channel focuses on providing content on Data Science, Artificial Intelligence, Machine Learning, Deep Learning, Computer Vision, Natural language processing, Generative AI, MLOPs, Python programming, etc. in English.
My mission is to provide inspiration, motivation & good quality education to students for learning and human development, and to become an expert in Artificial Intelligence, Machine Learning, Deep Learning, Computer Vision, Natural language processing, Generative AI, MLOPs, Python programming, and so on.
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