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 -Data clustering +Gradient descent +Machine learning for physical sciences +scikit-learn +Ulrike von Luxburg -tf-idf"

Positive matches

• 0.126 + - Class imbalance
• 0.036 + - Neural network
• 0.033 + - Recommender system
• 0.032 + - Neuron
• 0.023 + - Decision tree
• 0.016 + - Random forest
• 0.015 + - Learning
• 0.015 + - Boosting (machine learning)
• 0.014 + - Privacy and Deanonymization
• 0.013 + - Python/Modules
• 0.012 + - Future of work
• 0.012 + - skorch
• 0.012 + - Jupyter/notebook
• 0.011 + - Poker
• 0.011 + - IPython notebook
• 0.010 + - Regular expression
• 0.010 + - Python
• 0.009 + - Deep learning
• 0.009 + - Regex
• 0.008 + - Tim Hopper

Negative matches

• 0.027 + - Text analysis
• 0.015 + - Pointwise mutual information
• 0.013 + - Gensim
• 0.013 + - NLTK
• 0.006 + - Lexical feature selection
• 0.004 + - Natural language processing
• 0.003 + - Data analysis
• 0.001 + - Paper/Levy2014
• 0.001 + - Biomedical natural language processing
• 0.001 + - Skip-gram
• 0.001 + - GloVe
• 0.000 + - StanfordNLP
• 0.000 + - Paper/Levy2014a
• 0.000 + - CPython
• 0.000 + - Continuous embedding
• 0.000 + - Tomas Mikolov
• 0.000 + - Omer Levy
• 0.000 + - Paper/Perozzi2014
• 0.000 + - Paper
• 0.000 + - Yoav Goldberg