Search "+Peter Norvig +Automated machine learning +Class imbalance problem +Travelling salesman problem -Probability, Paradox, and the Reasonable Person Principle +Cross validation +Cluster analysis +Artificial neural network +Data clustering +Ulrike von Luxburg +Jupyter/notebook +scikit-learn -Poker -Learning +Python"

Positive matches

• 0.200 + - Machine learning
• 0.109 + - Class imbalance
• 0.026 + - IPython notebook
• 0.024 + - Gradient descent
• 0.022 + - Brain network
• 0.020 + - Recommender system
• 0.020 + - Decision tree
• 0.017 + - tfidf
• 0.015 + - skorch
• 0.014 + - IPython
• 0.014 + - Pajek
• 0.014 + - Artemy Kolchinsky
• 0.013 + - Jupyter
• 0.013 + - Deep learning
• 0.013 + - Random forest
• 0.013 + - Python/Modules
• 0.011 + - Boosting (machine learning)
• 0.010 + - Lexical feature selection
• 0.010 + - Tim Hopper
• 0.010 + - tf-idf

Negative matches

• 0.017 + - Michael Ramscar
• 0.017 + - How to study
• 0.002 + - Jonah Lehrer
• 0.002 + - 유재명
• 0.002 + - Thermostat
• 0.002 + - word2vec
• 0.002 + - Keras
• 0.002 + - Memorization
• 0.002 + - Practice
• 0.002 + - Willpower
• 0.002 + - Jürgen Schmidhuber
• 0.001 + - Research advices
• 0.001 + - Residual leanrning
• 0.001 + - Python#Modules_.26_Libraries
• 0.000 + - Generative adversarial network
• 0.000 + - Convolutional neural network
• 0.000 + - Marc'Aurelio Ranzato
• 0.000 + - Autoencoder