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) -Rob Schapire -Data clustering +Gradient descent +Yoav Freund -Lexical feature selection"

Positive matches

• 0.117 + - Class imbalance
• 0.033 + - Neural network
• 0.028 + - Neuron
• 0.025 + - Recommender system
• 0.022 + - Ulrike von Luxburg
• 0.020 + - scikit-learn
• 0.017 + - Ron Meir
• 0.015 + - Learning
• 0.013 + - tfidf
• 0.012 + - Future of work
• 0.012 + - Regular expression
• 0.012 + - IPython notebook
• 0.012 + - Privacy and Deanonymization
• 0.011 + - Gensim
• 0.011 + - NLTK
• 0.010 + - Poker
• 0.010 + - Jupyter/notebook
• 0.008 + - Decision tree
• 0.007 + - Regex
• 0.007 + - Random forest

Negative matches

• 0.017 + - Data analysis
• 0.012 + - Natural language processing
• 0.006 + - Convolutional neural network
• 0.004 + - NLP
• 0.004 + - Probability
• 0.002 + - spaCy
• 0.002 + - BookNLP
• 0.002 + - Christopher D. Manning
• 0.002 + - Biomedical natural language processing
• 0.002 + - Long short-term memory
• 0.001 + - Dialog act
• 0.001 + - Topic modeling
• 0.001 + - CNN
• 0.001 + - StanfordNLP
• 0.001 + - Residual Learning
• 0.001 + - Latent Dirichlet allocation
• 0.001 + - scispaCy
• 0.001 + - Sentence embedding
• 0.001 + - David Feldman
• 0.001 + - Topic model