Search "+Peter Norvig +Automated machine learning +Paradox +Travelling salesman problem +Boosting (machine learning) +Machine learning +Information theory +IPython notebook -Class imbalance -Simpson's paradox -Poker +IPython +Gradient descent +Lexical feature selection -Neuron"

Positive matches

• 0.065 + - Probability, Paradox, and the Reasonable Person Principle
• 0.035 + - Python
• 0.029 + - Probability
• 0.025 + - Jupyter/notebook
• 0.025 + - Pointwise mutual information
• 0.024 + - Python/Modules
• 0.022 + - Text analysis
• 0.021 + - tf-idf
• 0.018 + - Yoav Freund
• 0.018 + - Ron Meir
• 0.018 + - Rob Schapire
• 0.017 + - Natural language processing
• 0.017 + - SSH tunneling
• 0.017 + - Data analysis
• 0.014 + - Data science
• 0.010 + - Information Theory, Inference, and Learning Algorithms
• 0.010 + - Cross entropy
• 0.010 + - Recommender system
• 0.010 + - David Feldman
• 0.010 + - David MacKay

Negative matches

• 0.029 + - Neural network
• 0.003 + - Class imbalance problem
• 0.001 + - word2vec
• 0.001 + - sense2vec
• 0.001 + - Tomas Mikolov
• 0.001 + - Paper/Levy2014a
• 0.001 + - GloVe
• 0.001 + - Paper/Graves2014NTM
• 0.001 + - Clinical concept embedding
• 0.001 + - Google
• 0.001 + - Continuous embedding
• 0.001 + - Paper/Levy2014
• 0.001 + - Chris McCormick
• 0.001 + - Wolfgang Maass
• 0.001 + - TensorFlow
• 0.001 + - Attention (Deep learning)
• 0.000 + - Ivo Danihelka
• 0.000 + - Paper
• 0.000 + - Topic modeling
• 0.000 + - Neural Turing machine