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) +NLTK +Natural language processing -Residual Learning"

Positive matches

• 0.135 + - Class imbalance
• 0.041 + - Text analysis
• 0.039 + - Recommender system
• 0.036 + - tfidf
• 0.032 + - Lexical feature selection
• 0.032 + - Gradient descent
• 0.026 + - Ulrike von Luxburg
• 0.026 + - Data clustering
• 0.026 + - scikit-learn
• 0.020 + - Pointwise mutual information
• 0.020 + - Rob Schapire
• 0.020 + - Yoav Freund
• 0.020 + - Ron Meir
• 0.017 + - CNN
• 0.015 + - Privacy and Deanonymization
• 0.014 + - Gensim
• 0.014 + - Learning
• 0.013 + - Jupyter/notebook
• 0.012 + - Poker
• 0.012 + - IPython notebook

Negative matches

• 0.017 + - Residual leanrning
• 0.017 + - Convolutional neural network
• 0.014 + - Deep learning
• 0.007 + - Beer
• 0.006 + - Language
• 0.005 + - Meta learning
• 0.003 + - Machine translation
• 0.002 + - Amazon Elastic Compute Cloud
• 0.002 + - Probability
• 0.002 + - Autoencoder
• 0.002 + - Yann LeCun
• 0.002 + - Generative adversarial networks
• 0.002 + - Dropout
• 0.001 + - Generative adversarial network
• 0.001 + - TensorFlow
• 0.001 + - Quoc Le
• 0.001 + - Jürgen Schmidhuber
• 0.001 + - Geoffrey Hinton
• 0.001 + - Deep generative models
• 0.000 + - Marc'Aurelio Ranzato