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 +Gradient descent -EM algorithm -Ulrike von Luxburg +scikit-learn +Class imbalance -Learning"

Positive matches

• 0.032 + - Neural network
• 0.030 + - Neuron
• 0.025 + - Recommender system
• 0.021 + - Decision tree
• 0.015 + - Random forest
• 0.014 + - PyTorch
• 0.013 + - Python/Modules
• 0.012 + - skorch
• 0.011 + - Future of work
• 0.011 + - tf-idf
• 0.010 + - Poker
• 0.010 + - IPython notebook
• 0.010 + - tfidf
• 0.010 + - Boosting (machine learning)
• 0.010 + - Jupyter/notebook
• 0.010 + - Privacy and Deanonymization
• 0.009 + - Regular expression
• 0.009 + - Tim Hopper
• 0.009 + - Python
• 0.008 + - Regex

Negative matches

• 0.016 + - Michael Ramscar
• 0.016 + - How to study
• 0.008 + - Deep learning
• 0.004 + - Probability
• 0.002 + - Jonah Lehrer
• 0.002 + - 유재명
• 0.002 + - Autoencoder
• 0.002 + - Thermostat
• 0.002 + - Practice
• 0.002 + - Convolutional neural network
• 0.002 + - Yoshua Bengio
• 0.002 + - Jürgen Schmidhuber
• 0.001 + - Research advices
• 0.001 + - Differentiable neural computers
• 0.001 + - Residual leanrning
• 0.000 + - Quoc Le
• 0.000 + - Marc'Aurelio Ranzato
• 0.000 + - Residual Learning