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 +Future of work +Jupyter/notebook +Learning +Ulrike von Luxburg +Erik Brynjolfsson -Deep learning"

Positive matches

• 0.114 + - Class imbalance
• 0.030 + - Recommender system
• 0.026 + - Gradient descent
• 0.025 + - IPython notebook
• 0.024 + - Data clustering
• 0.021 + - Poker
• 0.017 + - How to study
• 0.017 + - Michael Ramscar
• 0.015 + - IPython
• 0.014 + - Artemy Kolchinsky
• 0.014 + - Jupyter
• 0.013 + - Privacy and Deanonymization
• 0.011 + - Boosting (machine learning)
• 0.011 + - scikit-learn
• 0.011 + - Tom Mitchell
• 0.011 + - Artificial intelligence
• 0.011 + - Technological unemployment
• 0.011 + - Skill gap
• 0.008 + - Decision tree
• 0.007 + - Python#Modules_.26_Libraries

Negative matches

• 0.019 + - Language
• 0.007 + - Reinforcement learning
• 0.005 + - Residual leanrning
• 0.004 + - Archetype
• 0.003 + - Q-learning
• 0.003 + - Cecilia Mascolo
• 0.002 + - Amazon EC2
• 0.002 + - Andy Connelly
• 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 + - Yann LeCun
• 0.002 + - Quoc Le
• 0.002 + - Generative adversarial networks
• 0.002 + - Long short-term memory
• 0.002 + - Paper/Gatys2015
• 0.002 + - Geoffrey Hinton