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Positive matches

• 0.208 + - Machine learning
• 0.146 + - Science
• 0.109 + - Class imbalance
• 0.026 + - IPython notebook
• 0.024 + - Ulrike von Luxburg
• 0.024 + - Data clustering
• 0.024 + - Gradient descent
• 0.022 + - Recommender system
• 0.019 + - How to study
• 0.018 + - Michael Ramscar
• 0.015 + - Artemy Kolchinsky
• 0.015 + - Jupyter
• 0.014 + - IPython
• 0.012 + - SSH tunneling
• 0.010 + - Boosting (machine learning)
• 0.009 + - Bookshelf
• 0.009 + - Research advices
• 0.008 + - Science policy
• 0.008 + - Programming interview
• 0.007 + - Paradox

Negative matches

• 0.024 + - Language
• 0.006 + - Amazon EC2
• 0.005 + - Reinforcement learning
• 0.004 + - Attention
• 0.004 + - Residual leanrning
• 0.004 + - NLP
• 0.003 + - Archetype
• 0.002 + - Deep generative models
• 0.002 + - Sentiment analysis
• 0.002 + - Geoffrey Hinton
• 0.002 + - Beer
• 0.002 + - Deep learning and graphs
• 0.002 + - Theano
• 0.002 + - Amazon Elastic Compute Cloud
• 0.002 + - Yann LeCun
• 0.002 + - Quoc Le
• 0.002 + - Long short-term memory
• 0.002 + - Generative adversarial networks
• 0.002 + - Paper/Gatys2015
• 0.002 + - Convolutional neural network