Search "+Peter Norvig +Automated machine learning +Class imbalance problem +Travelling salesman problem -Probability, Paradox, and the Reasonable Person Principle +Cross validation +Cluster analysis +Artificial neural network +Data clustering +Jupyter/notebook -Artemy Kolchinsky +Recommender system +Netflix prize +Poker -Deep learning"

Positive matches

• 0.232 + - Machine learning
• 0.121 + - Class imbalance
• 0.026 + - IPython notebook
• 0.024 + - Gradient descent
• 0.022 + - Ulrike von Luxburg
• 0.021 + - Brain network
• 0.015 + - IPython
• 0.014 + - Jupyter
• 0.013 + - Future of work
• 0.012 + - Learning
• 0.012 + - Boosting (machine learning)
• 0.009 + - Privacy and Deanonymization
• 0.008 + - scikit-learn
• 0.007 + - Data science
• 0.007 + - Spatial network
• 0.006 + - SSH tunneling
• 0.005 + - SSH
• 0.005 + - Python
• 0.005 + - Regular expression
• 0.004 + - Aging brain

Negative matches

• 0.019 + - Language
• 0.008 + - Reinforcement learning
• 0.007 + - 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 + - Machine translation
• 0.002 + - Geoffrey Hinton
• 0.002 + - Beer
• 0.002 + - Natural language processing
• 0.002 + - Amazon Elastic Compute Cloud
• 0.002 + - Yoshua Bengio
• 0.002 + - Generative adversarial networks
• 0.002 + - Long short-term memory
• 0.002 + - word2vec
• 0.002 + - Theano
• 0.002 + - Paper/Gatys2015