Search "+Peter Norvig +Automated machine learning +Paradox +Travelling salesman problem +Boosting (machine learning) +Machine learning +Information theory +IPython notebook +Jupyter/notebook +Data science +Cross entropy +Pointwise mutual information +Class imbalance problem +Lexical feature selection +IPython +Artemy Kolchinsky -Natural language processing"

Positive matches

• 0.087 + - Class imbalance
• 0.057 + - Probability, Paradox, and the Reasonable Person Principle
• 0.051 + - Text analysis
• 0.031 + - Python
• 0.030 + - Data analysis
• 0.030 + - Poker
• 0.029 + - Simpson's paradox
• 0.025 + - Probability
• 0.023 + - Computational social science
• 0.022 + - Python/Modules
• 0.020 + - tf-idf
• 0.017 + - SSH
• 0.017 + - SSH tunneling
• 0.017 + - Gradient descent
• 0.016 + - Rob Schapire
• 0.016 + - Yoav Freund
• 0.015 + - Ron Meir
• 0.013 + - Jupyter
• 0.011 + - Recommender system
• 0.011 + - David MacKay

Negative matches

• 0.010 + - CNN
• 0.006 + - Residual Learning
• 0.006 + - RNN
• 0.003 + - Residual leanrning
• 0.002 + - Research advices
• 0.002 + - BERT
• 0.002 + - Topic modeling
• 0.002 + - Sentiment analysis
• 0.002 + - scispaCy
• 0.002 + - Long short-term memory
• 0.002 + - Machine translation
• 0.002 + - BookNLP
• 0.002 + - Christopher D. Manning
• 0.002 + - NLP
• 0.001 + - Attention (Deep learning)
• 0.001 + - KoNLPy
• 0.001 + - fastText
• 0.001 + - Word embedding
• 0.001 + - Tomas Mikolov
• 0.001 + - Paper/Gatys2015