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 +Future of work +Jupyter/notebook +Learning +Ulrike von Luxburg -Michael Ramscar +Skill gap -Deep learning"

Positive matches

• 0.102 + - Class imbalance
• 0.024 + - Gradient descent
• 0.023 + - Data clustering
• 0.023 + - Recommender system
• 0.022 + - IPython notebook
• 0.019 + - Poker
• 0.019 + - Boosting (machine learning)
• 0.016 + - How to study
• 0.015 + - IPython
• 0.013 + - Artemy Kolchinsky
• 0.013 + - Jupyter
• 0.012 + - James Bessen
• 0.012 + - Heidi Shierholz
• 0.012 + - Andrew Weaver
• 0.012 + - Peter Cappelli
• 0.011 + - Regular expression
• 0.010 + - Erik Brynjolfsson
• 0.010 + - Tom Mitchell
• 0.010 + - Artificial intelligence
• 0.010 + - Technological unemployment

Negative matches

• 0.020 + - Language
• 0.006 + - Residual leanrning
• 0.005 + - Attention
• 0.004 + - Reinforcement learning
• 0.004 + - Amazon EC2
• 0.002 + - Modeling animal behaviors with reinforcement learning
• 0.002 + - Cecilia Mascolo
• 0.002 + - Amazon Web Services
• 0.002 + - Archetype
• 0.002 + - Paper/Hochreiter1997
• 0.002 + - Geoffrey Hinton
• 0.002 + - Deep learning and graphs
• 0.002 + - Natural language processing
• 0.002 + - Neural doodle
• 0.002 + - Amazon Elastic Compute Cloud
• 0.002 + - Yann LeCun
• 0.002 + - Long short-term memory
• 0.002 + - word2vec
• 0.002 + - Autoencoder
• 0.002 + - Theano