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 -Artemy Kolchinsky -Class imbalance -tf-idf"

Positive matches

• 0.069 + - Regular expression
• 0.022 + - Data clustering
• 0.022 + - Ulrike von Luxburg
• 0.021 + - IPython notebook
• 0.021 + - Gradient descent
• 0.019 + - Decision tree
• 0.015 + - Recommender system
• 0.014 + - IPython
• 0.013 + - PyTorch
• 0.013 + - Python/Modules
• 0.012 + - Random forest
• 0.012 + - Jupyter
• 0.012 + - SSH tunneling
• 0.011 + - Python
• 0.010 + - Future of work
• 0.010 + - skorch
• 0.010 + - Learning
• 0.008 + - Boosting (machine learning)
• 0.008 + - Paradox
• 0.008 + - Tim Hopper

Negative matches

• 0.024 + - Text analysis
• 0.015 + - Pointwise mutual information
• 0.011 + - Gensim
• 0.011 + - NLTK
• 0.009 + - Lexical feature selection
• 0.003 + - Natural language processing
• 0.002 + - Probability
• 0.002 + - Data analysis
• 0.001 + - word2vec
• 0.001 + - Rob Schapire
• 0.001 + - Generative adversarial network
• 0.001 + - GloVe
• 0.001 + - Paper/Levy2014a
• 0.001 + - sense2vec
• 0.000 + - Recurrent neural network
• 0.000 + - StanfordNLP
• 0.000 + - NLP
• 0.000 + - RNN
• 0.000 + - WordRank
• 0.000 + - Long short-term memory