Predicting Student Performance with Ruby ML
Build a student performance prediction system in Ruby. Feature engineering, model training, and practical risk assessment.
Practical machine learning implementations, algorithms, and real-world applications
Build a student performance prediction system in Ruby. Feature engineering, model training, and practical risk assessment.
Learn Item Response Theory and the Rasch model with Python. Practical examples for test analysis, adaptive testing, and measurement in education and psychology.
Create a spam filter or text classifier in Ruby using Bayes' theorem. Complete implementation with training, classification, and testing code.
Learn to integrate machine learning into Ruby apps using ruby-fann for neural networks. Working examples, training tips, and when Ruby ML actually makes sense.
Real applications of machine learning in healthcare - from diagnosis to drug discovery. What works, what doesn't, and where we're headed.