#HumanLearning vs # StatLearning vs #MachineLearning vs #AILearning

Consider the following hashtags:

#HumanLearning

1. Read it.
2. Write it.
3. Say it.
4. Use it.
5. Code it.

#StatLearning

1. Random sample of data from a population
2. Model
   1. T-test, T Confidence Interval
   2. ANOVA
   3. Regression or Logistic Regression
3. Evaluate
   1. Statistical Significance, Practical Significance, Effect Size
   2. Assume unbiased
4. Explain

#MachineLearning

1. Larger observational data from a population, do we trust that the data is representative of the population?
2. Split the data
   1. Training
   2. Validation
   3. Testing
3. Model
   1. kNN, Naive Bayes, Decision Trees, Boosting, Bagging Random Forests, GBM, SVM, NN
      
4. Evaluate
   1. Model Accuracy, Validation Accuracy, Testing Accuracy, MSE
   2. Bias
5. Explain

#AILearning

1. Input data for prediction
   1. Text
   2. Image
   3. Audio
   4. Video
2. Prompt the AI
   1. Introduce yourself
   2. Explain the problem
   3. Give directions for the presentation of the solution
   4. Specify the expected results
3. Continue the discussion until you are satisfied