Search "+Peter Norvig +Automated machine learning +Paradox +Travelling salesman problem +Boosting (machine learning) +Machine learning +Information theory +IPython notebook +Jupyter/notebook +Recommender system +Artemy Kolchinsky -Poker +Lexical feature selection +Class imbalance problem +Jupyter +Ron Meir +Data science -Natural language processing"

Positive matches

• 0.092 + - Class imbalance
• 0.049 + - Probability, Paradox, and the Reasonable Person Principle
• 0.032 + - IPython
• 0.029 + - Netflix prize
• 0.029 + - Probability
• 0.029 + - Polynote
• 0.028 + - Simpson's paradox
• 0.023 + - Computational social science
• 0.022 + - Data analysis
• 0.020 + - Gradient descent
• 0.018 + - SSH tunneling
• 0.017 + - tf-idf
• 0.016 + - Pointwise mutual information
• 0.015 + - Yoav Freund
• 0.015 + - Rob Schapire
• 0.015 + - Text analysis
• 0.011 + - Industry-Academic Partnership
• 0.010 + - SSH
• 0.010 + - Python
• 0.009 + - Information Theory, Inference, and Learning Algorithms

Negative matches

• 0.012 + - CNN
• 0.005 + - Residual leanrning
• 0.004 + - Residual Learning
• 0.004 + - RNN
• 0.002 + - Paper/Gatys2015
• 0.002 + - StanfordNLP
• 0.002 + - BERT
• 0.002 + - BookNLP
• 0.002 + - Sentiment analysis
• 0.002 + - Topic modeling
• 0.002 + - Sentence embedding
• 0.001 + - scispaCy
• 0.001 + - Christopher D. Manning
• 0.001 + - NLP
• 0.001 + - Cecilia Mascolo
• 0.001 + - Tomas Mikolov
• 0.001 + - Latent Dirichlet allocation
• 0.001 + - KenLM
• 0.001 + - Dialog act
• 0.001 + - Long short-term memory