Machine Learning

  Unit I (B) The Machine Learning Landscape 1.      Main Challenges of Machine Learning 2.      Insufficient Quantity of Training Data 3.      Nonrepresentative Training Data 4.      Poor-Quality Data 5.      Irrelevant Features 6.      Overfitting the Training Data 7.      Underfitting the Training Data 8.      Stepping Back 9.      Testing and Validating  

                                                                                      Unit I (B) The Machine Learning Landscape 1.       7.      Main Challenges of Machine Learning 8.      Insufficient Quantity of Training Data 9.      Nonrepresentative Training Data 10.   Poor-Quality Data 11.   Irrelevant Features 12.   Overfitting the Training Data 13.   Underfitting the Training Data 14.   Stepping Back 15.   Testing and Validating