Search "+Peter Norvig +Automated machine learning +Paradox +Travelling salesman problem +Boosting (machine learning) +Machine learning +Information theory +IPython notebook +Jupyter/notebook +Probability, Paradox, and the Reasonable Person Principle +Poker +David Feldman +Recommender system +IPython -Netflix prize -Learning"

Positive matches

• 0.051 + - Lexical feature selection
• 0.041 + - Probability
• 0.034 + - Class imbalance
• 0.033 + - Class imbalance problem
• 0.033 + - Python
• 0.031 + - Simpson's paradox
• 0.026 + - SSH tunneling
• 0.023 + - Python/Modules
• 0.018 + - Data science
• 0.017 + - Yoav Freund
• 0.017 + - Ron Meir
• 0.017 + - Rob Schapire
• 0.016 + - Artemy Kolchinsky
• 0.014 + - Gradient descent
• 0.014 + - Jupyter
• 0.010 + - Python/Beautiful soup
• 0.009 + - David MacKay
• 0.009 + - Information Theory, Inference, and Learning Algorithms
• 0.009 + - Future of work
• 0.008 + - Pointwise mutual information

Negative matches

• 0.016 + - Michael Ramscar
• 0.016 + - How to study
• 0.013 + - Deep learning
• 0.002 + - Jonah Lehrer
• 0.002 + - 유재명
• 0.002 + - Autoencoder
• 0.002 + - word2vec
• 0.002 + - Jürgen Schmidhuber
• 0.002 + - Quoc Le
• 0.002 + - Practice
• 0.002 + - Marc'Aurelio Ranzato
• 0.002 + - Research advices
• 0.002 + - Residual leanrning
• 0.001 + - Residual Learning
• 0.001 + - Theano
• 0.000 + - Convolutional neural network
• 0.000 + - Thermostat
• 0.000 + - Differentiable neural computers