Machine Learning With Python
Introduction
to Python on Machine Learning, Flask & Making a Basic API,
Receiving Data through GET & POST Request
No lessons are available yet.
Content
- Making an HTML Form to Send inputs
- Deploying Machine Learning Model using Flask
- ML Models
- Importing Data & Data Visualization
- Feature Scaling & Encoding
- Model Fitting and Getting the Feature importance
- Balancing the dataset and Feature Selection
- Deploying & Training the Model and Showing Prediction on UI
- Containerizing Model using Docker
- Coding the Dockerfile
- Containerizing
- Serverless and AWS Function as a Service (FaaS) of Serverless
- AWS Serverless Adding Configs
- Deploy the Project on AWS
- Deploying ML Model using AWS Lambda
- Deploying the Model SageMaker
- Instance Type
- Built in Algorithm
- Frameworks Offered
- AWS Ground Truth and NEO
- Difference API Leves
- Making An S3 Bucket
- Spinning Jupyter Notebook in Sagemaker
- Implementing Xg Boost Using Sagemaker
- Data importing
- Understanding the Folder Structure AWS Accepts
- Basic Setup and Model Python File
- Basic Imports and Upload to S3
- Model Building
- Fitting & End Point Creation and many more