Search "+Peter Norvig +Automated machine learning +Class imbalance problem +Travelling salesman problem -Probability, Paradox, and the Reasonable Person Principle +Cross validation +Cluster analysis +Machine learning +Machine learning for healthcare +tf-idf +Boosting (machine learning) +IPython notebook +NLTK +Learning +Gensim -Natural language processing"

Positive matches

• 0.115 + - Class imbalance
• 0.049 + - tfidf
• 0.034 + - word2vec
• 0.033 + - Lexical feature selection
• 0.025 + - Recommender system
• 0.025 + - Gradient descent
• 0.024 + - Text analysis
• 0.022 + - Data clustering
• 0.022 + - Ulrike von Luxburg
• 0.021 + - Pointwise mutual information
• 0.021 + - scikit-learn
• 0.020 + - Jupyter/notebook
• 0.019 + - Deep learning
• 0.017 + - Ron Meir
• 0.017 + - Poker
• 0.016 + - How to study
• 0.016 + - Yoav Freund
• 0.016 + - Michael Ramscar
• 0.016 + - Rob Schapire
• 0.013 + - SSH tunneling

Negative matches

• 0.017 + - CNN
• 0.004 + - Residual Learning
• 0.002 + - fastText
• 0.002 + - String metric
• 0.002 + - KenLM
• 0.002 + - Kyunghyun Cho
• 0.002 + - Word segmentation
• 0.002 + - BERT
• 0.002 + - Latent Dirichlet allocation
• 0.002 + - Dialog act
• 0.002 + - BookNLP
• 0.002 + - Word embedding
• 0.002 + - Christopher D. Manning
• 0.002 + - KoNLPy
• 0.002 + - Topic modeling
• 0.002 + - Probability
• 0.002 + - Sentence embedding
• 0.002 + - Long short-term memory
• 0.002 + - Sentiment analysis
• 0.001 + - Topic model