MLDA

MLDA

1. what is Predictive analytics

   • Diagram

2. Applications

   • what's ml
     • How does it work
       • What can go wrong
         • under fitting
           • overfitting
             • graphs
               • CRISPDM
                 • lifecycle of predective analytics
                   • 6 steps
                     • predictive analytics tools
                       • data analytics to insights to decision
                         • case study
                           • motor insurance case study
                             • access feseability
                               • claim prdiction
                             • Illustration to create an ABT
                               • ABT DESIGN
                               • MOTOR insurance fraud
                                 • design and implementing features
                                   • key feature for design and implementation
                                     • different types of data and features
                                       • handling time and examples
                                         • 2 examples
                                           • majorly consider motor insurance fraud
     • Supervised ml
     • Unsupervised

3. UNIT :01 TOPICS