Understanding Machine Learning Framework

 

Machine Learning Models involve Feature Engineering, Evaluating Model Performance, Scalability, Data Preparation Capabilities, Basic and Advanced Algorithms used for making AI applications.

 

Lifecycle of deploying Machine Learning Model involves –

 

  • Define KPIs
  • Retrieving Data
  • Data Preprocessing & Cleansing
  • Data Exploration & Visualization
  • Data Modeling
  • Model Deployment

 

Build, Train and Deployment of Model Comprises of –

 

  • Collection and Preparation of Data
  • Algorithm and Framework Selection
  • Tune Model to get Predictions
  • API Building and Integration of Model with Application
  • Deployment of Application on Infrastructure

 

Real-Time Applications of Machine Learning exists in –

 

  • Prediction of EarthQuakes and Droughts
  • Object and Face Detection
  • Stock Marketing and Financial Trading
  • Cyber Security and Banking Sectors
  • Healthcare for Diagnosis