MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 15 lectures (3h 15m) | Size: 1.14 GB
Learn complete end to end Machine Learning Models Deployment using Python Flask Web Application on Microsoft Azure.
Deploying Flask WebApp on Azure
Integrating Python ML Model into WebApp
Basic Machine Learning (Scikit-Learn)
Free or Paid Microsoft Azure Account
In this course, you will be learning, how to deploy Machine Learning Models using Python Flask on Microsoft Azure from scratch. Initially, we will learn the entire Machine Learning pipeline using Jupyter Notebook including Exploratory Data Analysis. Then for intuition, we will train 6 Machine Learning (Classification) models, and save them. After some tests, we will generate a productional code for prediction for all 6 Machine Learning Models.
Now the golden lectures start. We will develop the Frontend of Web Application using HTML / CSS from scratch, giving an end-to-end idea of what's happening in the design structure. Then, we will develop the backend on Flask using Python and integrate it with our Frontend. After some tests of a fully functional Machine Learning Web App on the system, we will move ahead to our main goal, Deployment on Microsoft Azure. Where many students face problems and server issues. Don't worry with one simple trick you won't face any server issues on Azure.
So without wasting any further minutes, grab your course, and learn deployment from scratch in 2-3 days at an Easy pace.
And here's the bonus, in the event of unfortunate success in deployment, the instructor will always be available to help you around the issues.
Python Developers looking for ML Models Deployment
Web Developers looking for integrating ML Models into WebApp
ML Enthusiasts curious about how to deploy models on WebApp
Cloud Enthusiast looking for deploying ML Models or WebApps to Microsoft Azure
Industrial Machine Learning Pipeline