Search "+Peter Norvig +Automated machine learning +Paradox +Travelling salesman problem +Boosting (machine learning) +Machine learning +Information theory +IPython notebook +Probability -Recommender system +David MacKay +Python +Books +Lexical feature selection -Natural language processing"

Positive matches

• 0.076 + - Probability, Paradox, and the Reasonable Person Principle
• 0.033 + - Simpson's paradox
• 0.030 + - Home
• 0.028 + - Class imbalance problem
• 0.026 + - Data analysis
• 0.025 + - Jupyter/notebook
• 0.023 + - Pointwise mutual information
• 0.022 + - Paper/MacKay1991
• 0.022 + - Probability theory
• 0.022 + - Probability distribution
• 0.022 + - Poker
• 0.018 + - Yoav Freund
• 0.018 + - Rob Schapire
• 0.018 + - Ron Meir
• 0.018 + - tf-idf
• 0.017 + - Pajek
• 0.016 + - Text analysis
• 0.015 + - IPython
• 0.015 + - Class imbalance
• 0.013 + - Information Theory, Inference, and Learning Algorithms

Negative matches

• 0.032 + - Netflix prize
• 0.016 + - CNN
• 0.008 + - Residual Learning
• 0.006 + - Residual leanrning
• 0.003 + - Amazon Elastic Compute Cloud
• 0.002 + - BERT
• 0.002 + - Sentence embedding
• 0.002 + - Kyunghyun Cho
• 0.002 + - Long short-term memory
• 0.002 + - Word embedding
• 0.002 + - Christopher D. Manning
• 0.002 + - Topic modeling
• 0.002 + - Paper/Gatys2015
• 0.002 + - Neural network
• 0.002 + - spaCy
• 0.002 + - Dialog act
• 0.002 + - Sentiment analysis
• 0.001 + - fastText
• 0.001 + - BookNLP
• 0.001 + - KoNLPy