Search "+Peter Norvig +Automated machine learning +Class imbalance problem +Travelling salesman problem -Probability, Paradox, and the Reasonable Person Principle +Cross validation +Cluster analysis +Machine learning +Machine learning for healthcare +tf-idf +Boosting (machine learning) +Learning +Gensim +IPython +Text analysis +Yoav Freund -Probability"

Positive matches

• 0.116 + - Class imbalance
• 0.051 + - Lexical feature selection
• 0.032 + - Data analysis
• 0.030 + - tfidf
• 0.029 + - word2vec
• 0.029 + - IPython notebook
• 0.028 + - Gradient descent
• 0.028 + - Recommender system
• 0.022 + - Python/Modules
• 0.022 + - scikit-learn
• 0.021 + - Data clustering
• 0.021 + - Python
• 0.021 + - Deep learning
• 0.020 + - Ulrike von Luxburg
• 0.019 + - Pointwise mutual information
• 0.019 + - Science
• 0.016 + - Poker
• 0.016 + - Ron Meir
• 0.015 + - Regular expression
• 0.015 + - How to study

Negative matches

• 0.020 + - Probability distribution
• 0.020 + - Probability theory
• 0.001 + - Edwin Thompson Jaynes
• 0.001 + - Probability Theory: The Logic of Science
• 0.001 + - Bayesian inference
• 0.001 + - Stochastic process
• 0.001 + - Frequentist inference
• 0.001 + - Sure Thing hypothesis
• 0.000 + - Beta distribution
• 0.000 + - Dirichlet distribution
• 0.000 + - Jupyter