Search "+Peter Norvig +Automated machine learning +Poker -Information theory"

Positive matches

• 0.260 + - Machine learning
• 0.133 + - Paradox
• 0.058 + - Probability
• 0.048 + - IPython notebook
• 0.045 + - Jupyter/notebook
• 0.042 + - Probability, Paradox, and the Reasonable Person Principle
• 0.042 + - Travelling salesman problem
• 0.033 + - Class imbalance
• 0.024 + - Gradient descent
• 0.023 + - Class imbalance problem
• 0.013 + - Learning
• 0.006 + - Andrew Ng
• 0.006 + - GraphLab
• 0.006 + - EM algorithm
• 0.006 + - Carlos Guestrin
• 0.006 + - Training dataset
• 0.006 + - Michael I. Jordan
• 0.006 + - scikit-learn
• 0.006 + - Image completion
• 0.006 + - Weka

Negative matches

• 0.154 + - Lexical feature selection
• 0.032 + - Text analysis
• 0.031 + - David MacKay
• 0.031 + - Kullback–Leibler divergence
• 0.031 + - Information Theory, Inference, and Learning Algorithms
• 0.031 + - Cross entropy
• 0.031 + - Pointwise mutual information
• 0.031 + - Gibbs' inequality
• 0.031 + - David Feldman
• 0.003 + - Recommender system
• 0.003 + - Data analysis
• 0.003 + - tf-idf
• 0.001 + - Ilya Sutskever
• 0.001 + - Convolutional neural network
• 0.001 + - Natural language processing
• 0.001 + - Future of work
• 0.001 + - Regex
• 0.001 + - Neural network
• 0.001 + - Residual Learning
• 0.000 + - Language