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 +Yoav Freund +tfidf +Data clustering -NLTK"

Positive matches

• 0.117 + - Class imbalance
• 0.026 + - Gradient descent
• 0.024 + - Recommender system
• 0.023 + - scikit-learn
• 0.022 + - Ulrike von Luxburg
• 0.018 + - Text analysis
• 0.017 + - Ron Meir
• 0.015 + - Learning
• 0.014 + - Gensim
• 0.014 + - Pointwise mutual information
• 0.012 + - Future of work
• 0.012 + - Regular expression
• 0.012 + - Privacy and Deanonymization
• 0.011 + - IPython notebook
• 0.010 + - Poker
• 0.010 + - Jupyter/notebook
• 0.007 + - Regex
• 0.007 + - Random forest
• 0.007 + - Decision tree
• 0.006 + - Deep learning

Negative matches

• 0.028 + - Natural language processing
• 0.004 + - Probability
• 0.004 + - Biomedical natural language processing
• 0.002 + - scispaCy
• 0.002 + - NLP
• 0.002 + - Lexical feature selection
• 0.002 + - spaCy
• 0.002 + - StanfordNLP
• 0.001 + - Residual Learning
• 0.001 + - Sentiment analysis
• 0.001 + - CNN
• 0.001 + - Archetype
• 0.001 + - Convolutional neural network
• 0.001 + - Musical composition
• 0.000 + - Long short-term memory
• 0.000 + - LSTM
• 0.000 + - Paper/Gatys2015
• 0.000 + - Attention (Deep learning)
• 0.000 + - Amazon Elastic Compute Cloud