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) +NLTK +Pointwise mutual information +Poker -Natural language processing"

Positive matches

• 0.124 + - Class imbalance
• 0.062 + - Text analysis
• 0.061 + - Lexical feature selection
• 0.037 + - Information theory
• 0.032 + - Recommender system
• 0.031 + - tfidf
• 0.030 + - Gradient descent
• 0.026 + - scikit-learn
• 0.024 + - Ulrike von Luxburg
• 0.024 + - Data clustering
• 0.018 + - Yoav Freund
• 0.018 + - Rob Schapire
• 0.018 + - Ron Meir
• 0.015 + - Privacy and Deanonymization
• 0.014 + - Learning
• 0.014 + - Gensim
• 0.013 + - Jupyter/notebook
• 0.011 + - IPython notebook
• 0.011 + - Future of work
• 0.011 + - Data analysis

Negative matches

• 0.017 + - CNN
• 0.008 + - Residual Learning
• 0.005 + - Residual leanrning
• 0.003 + - Amazon Elastic Compute Cloud
• 0.002 + - BERT
• 0.002 + - String metric
• 0.002 + - BookNLP
• 0.002 + - Christopher D. Manning
• 0.002 + - KoNLPy
• 0.002 + - Topic modeling
• 0.002 + - Sentence embedding
• 0.002 + - Kyunghyun Cho
• 0.002 + - Recurrent neural network
• 0.002 + - Latent Dirichlet allocation
• 0.002 + - Word segmentation
• 0.002 + - Word embedding
• 0.002 + - Sentiment analysis
• 0.002 + - fastText
• 0.002 + - KenLM
• 0.002 + - Dialog act