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 +Poker -Class imbalance -Learning"

Positive matches

• 0.028 + - Gradient descent
• 0.028 + - IPython notebook
• 0.025 + - Ulrike von Luxburg
• 0.021 + - Recommender system
• 0.017 + - IPython
• 0.016 + - Artemy Kolchinsky
• 0.015 + - Jupyter
• 0.014 + - Boosting (machine learning)
• 0.013 + - Regular expression
• 0.011 + - Regex
• 0.010 + - Privacy and Deanonymization
• 0.010 + - Future of work
• 0.009 + - scikit-learn
• 0.008 + - Neural network
• 0.007 + - SSH tunneling
• 0.005 + - tf-idf
• 0.005 + - Random forest
• 0.004 + - Graph matching
• 0.004 + - Training dataset
• 0.004 + - SSH

Negative matches

• 0.018 + - How to study
• 0.018 + - Michael Ramscar
• 0.014 + - Deep learning
• 0.002 + - Yoshua Bengio
• 0.002 + - Residual leanrning
• 0.002 + - Jürgen Schmidhuber
• 0.002 + - Jonah Lehrer
• 0.002 + - 유재명
• 0.002 + - Convolutional neural network
• 0.002 + - Marc'Aurelio Ranzato
• 0.002 + - TensorFlow
• 0.002 + - Generative adversarial network
• 0.002 + - Recurrent neural network
• 0.001 + - Keras
• 0.001 + - Brain and deep learning
• 0.001 + - Residual Learning
• 0.001 + - Machine learning for physical sciences
• 0.001 + - Closure tools
• 0.001 + - Variational Autoencoder
• 0.001 + - t-SNE