Search "+Peter Norvig +Automated machine learning +Class imbalance problem +Travelling salesman problem -Probability, Paradox, and the Reasonable Person Principle +Cross validation +Cluster analysis +Computer science -Ulrike von Luxburg +Class imbalance +scikit-learn +tf-idf +PyTorch -Gensim"

Positive matches

• 0.230 + - Machine learning
• 0.048 + - skorch
• 0.037 + - PyTorch-BigGraph
• 0.036 + - Decision tree
• 0.030 + - Text analysis
• 0.025 + - Data clustering
• 0.023 + - Gradient descent
• 0.022 + - Recommender system
• 0.020 + - tfidf
• 0.015 + - Random forest
• 0.014 + - NLTK
• 0.013 + - Boosting (machine learning)
• 0.013 + - Jupyter/notebook
• 0.013 + - Tim Hopper
• 0.012 + - Natural language processing
• 0.012 + - IPython notebook
• 0.012 + - Python/Modules
• 0.012 + - Poker
• 0.012 + - Python
• 0.011 + - Interdisciplinary research

Negative matches

• 0.035 + - word2vec
• 0.003 + - Hierarchical softmax
• 0.002 + - Tomas Mikolov
• 0.002 + - Probability
• 0.002 + - Continuous embedding
• 0.002 + - wiki2vec
• 0.002 + - Graph embedding
• 0.001 + - WordRank
• 0.001 + - Paper/Hamilton2016
• 0.001 + - Finkbeiner test
• 0.001 + - Ilya Sutskever
• 0.001 + - Clinical concept embedding
• 0.001 + - Paper/Perozzi2014
• 0.001 + - Network geometry
• 0.001 + - Google
• 0.001 + - Dan Jurafsky
• 0.001 + - Omer Levy
• 0.001 + - Skip-gram
• 0.001 + - Paper/Levy2014
• 0.001 + - Softmax function