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 +Jupyter/notebook +Artemy Kolchinsky +Boosting (machine learning) +Learning -Deep learning"

Positive matches

• 0.124 + - Class imbalance
• 0.033 + - Recommender system
• 0.029 + - Gradient descent
• 0.024 + - IPython notebook
• 0.024 + - Ulrike von Luxburg
• 0.020 + - Poker
• 0.018 + - Yoav Freund
• 0.018 + - Rob Schapire
• 0.018 + - Ron Meir
• 0.017 + - How to study
• 0.017 + - Michael Ramscar
• 0.015 + - Privacy and Deanonymization
• 0.014 + - Jupyter
• 0.013 + - IPython
• 0.012 + - scikit-learn
• 0.011 + - Future of work
• 0.010 + - Regular expression
• 0.008 + - Random forest
• 0.008 + - Data science
• 0.008 + - Regex

Negative matches

• 0.017 + - Language
• 0.008 + - Reinforcement learning
• 0.006 + - Residual leanrning
• 0.003 + - Q-learning
• 0.003 + - Amazon EC2
• 0.003 + - Andy Connelly
• 0.003 + - Archetype
• 0.002 + - Attention
• 0.002 + - Modeling animal behaviors with reinforcement learning
• 0.002 + - Machine translation
• 0.002 + - Natural language processing
• 0.002 + - Beer
• 0.002 + - Amazon Elastic Compute Cloud
• 0.002 + - Yoshua Bengio
• 0.002 + - Yann LeCun
• 0.002 + - Generative adversarial networks
• 0.002 + - Long short-term memory
• 0.002 + - Paper/Gatys2015
• 0.002 + - Geoffrey Hinton
• 0.002 + - Dropout