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 -Poker +Jupyter/notebook +Regex +scikit-learn +tfidf +Probability +Learning -Ulrike von Luxburg +Gradient descent -tf-idf"

Positive matches

• 0.089 + - Class imbalance
• 0.063 + - Regular expression
• 0.036 + - Neural network
• 0.025 + - Neuron
• 0.020 + - Data clustering
• 0.020 + - IPython notebook
• 0.019 + - Probability theory
• 0.019 + - Probability distribution
• 0.018 + - Deep learning
• 0.017 + - Recommender system
• 0.016 + - Random forest
• 0.014 + - How to study
• 0.014 + - Michael Ramscar
• 0.013 + - Boosting (machine learning)
• 0.012 + - IPython
• 0.012 + - Artemy Kolchinsky
• 0.011 + - Jupyter
• 0.011 + - Decision tree
• 0.010 + - skorch
• 0.009 + - Python/Modules

Negative matches

• 0.017 + - Text analysis
• 0.016 + - Pointwise mutual information
• 0.010 + - Gensim
• 0.010 + - NLTK
• 0.005 + - Lexical feature selection
• 0.003 + - Natural language processing
• 0.002 + - Data analysis
• 0.001 + - Information visualization
• 0.000 + - Paper/Hamilton2016
• 0.000 + - Biomedical natural language processing
• 0.000 + - CPython
• 0.000 + - sense2vec
• 0.000 + - WordRank
• 0.000 + - Paper/Levy2014a
• 0.000 + - scispaCy
• 0.000 + - Chris McCormick
• 0.000 + - David Feldman
• 0.000 + - R
• 0.000 + - StanfordNLP
• 0.000 + - Paper/Levy2014