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 +Gradient descent -Ron Meir -Neuron"

Positive matches

• 0.125 + - Class imbalance
• 0.035 + - tfidf
• 0.033 + - word2vec
• 0.028 + - Recommender system
• 0.026 + - Text analysis
• 0.025 + - scikit-learn
• 0.024 + - Ulrike von Luxburg
• 0.024 + - Data clustering
• 0.023 + - Pointwise mutual information
• 0.019 + - Lexical feature selection
• 0.018 + - Yoav Freund
• 0.018 + - Rob Schapire
• 0.015 + - Privacy and Deanonymization
• 0.013 + - Learning
• 0.013 + - NLTK
• 0.012 + - Regular expression
• 0.012 + - Future of work
• 0.011 + - Jupyter/notebook
• 0.011 + - Poker
• 0.011 + - IPython notebook

Negative matches

• 0.030 + - Neural network
• 0.002 + - Neural Turing machine
• 0.001 + - Long short-term memory
• 0.001 + - Gender bias
• 0.001 + - Paper/Graves2014NTM
• 0.000 + - Rami Al-Rfou
• 0.000 + - Paper/Bahdanau2015
• 0.000 + - Ivo Danihelka
• 0.000 + - KoNLPy
• 0.000 + - Sentiment analysis
• 0.000 + - Topic modeling
• 0.000 + - Paper/Hochreiter1997
• 0.000 + - Jack Terwilliger
• 0.000 + - Recurrent neural network
• 0.000 + - Attention (Deep learning)
• 0.000 + - Google
• 0.000 + - Wolfgang Maass
• 0.000 + - GloVe