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 -Data clustering +Jupyter/notebook +IPython notebook +Jupyter +Poker +scikit-learn -Learning"

Positive matches

• 0.109 + - Class imbalance
• 0.043 + - IPython
• 0.032 + - Polynote
• 0.025 + - SSH tunneling
• 0.024 + - Gradient descent
• 0.022 + - Ulrike von Luxburg
• 0.022 + - Python
• 0.021 + - Recommender system
• 0.018 + - Decision tree
• 0.015 + - Artemy Kolchinsky
• 0.015 + - Data science
• 0.015 + - Random forest
• 0.014 + - PyTorch
• 0.013 + - Python/Modules
• 0.011 + - tfidf
• 0.011 + - Privacy and Deanonymization
• 0.011 + - Future of work
• 0.011 + - tf-idf
• 0.011 + - Paradox
• 0.011 + - Regular expression

Negative matches

• 0.016 + - Michael Ramscar
• 0.016 + - How to study
• 0.009 + - Deep learning
• 0.002 + - Jonah Lehrer
• 0.002 + - 유재명
• 0.002 + - Quoc Le
• 0.002 + - Practice
• 0.002 + - Marc'Aurelio Ranzato
• 0.002 + - Jürgen Schmidhuber
• 0.002 + - word2vec
• 0.001 + - Research advices
• 0.001 + - Residual Learning
• 0.001 + - Differentiable neural computers
• 0.001 + - Residual leanrning
• 0.001 + - Autoencoder
• 0.001 + - Paper/Vincent2010
• 0.001 + - Probability
• 0.000 + - Convolutional neural network
• 0.000 + - Keras
• 0.000 + - Thermostat