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) +Gensim +scikit-learn -Class imbalance -Yoav Freund -NLTK"

Positive matches

• 0.033 + - word2vec
• 0.027 + - Gradient descent
• 0.025 + - tfidf
• 0.024 + - Text analysis
• 0.023 + - Recommender system
• 0.022 + - Data clustering
• 0.022 + - Ulrike von Luxburg
• 0.020 + - Decision tree
• 0.018 + - Pointwise mutual information
• 0.017 + - Ron Meir
• 0.016 + - Rob Schapire
• 0.016 + - Random forest
• 0.015 + - Learning
• 0.014 + - Python/Modules
• 0.014 + - Privacy and Deanonymization
• 0.013 + - PyTorch
• 0.013 + - Future of work
• 0.012 + - IPython notebook
• 0.011 + - Regular expression
• 0.011 + - Lexical feature selection

Negative matches

• 0.028 + - Natural language processing
• 0.005 + - Biomedical natural language processing
• 0.003 + - Probability
• 0.003 + - scispaCy
• 0.002 + - StanfordNLP
• 0.002 + - NLP
• 0.001 + - spaCy
• 0.001 + - CNN
• 0.001 + - Convolutional neural network
• 0.001 + - Musical composition
• 0.001 + - Atwood's law
• 0.001 + - Sentiment analysis
• 0.001 + - Generative adversarial network
• 0.001 + - Archetype
• 0.000 + - Long short-term memory
• 0.000 + - Paper/Gatys2015
• 0.000 + - Attention (Deep learning)
• 0.000 + - Amazon Elastic Compute Cloud