KDnuggets Poll - Top Data Science and Machine Learning Methods Used in 2018/2019
* Required
Which Data Science / Machine Learning methods and algorithms did you use in 2018/2019 for a real-world application?
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Anomaly / Deviation Detection
Association Rules
Bagging
Bayesian Methods
Boosting
Clustering
Decision Trees / Rules
Ensemble Methods
Expectation-Maximization (EM)
Factor Analysis
Generative Adversarial Networks (GAN)
Genetic / Evolutionary Algorithms & Methods
Gradient Boosted Machines
Graph / Link / Social Network Analysis
Hidden Markov Models (HMM)
K-Nearest Neighbours
Markov Logic Networks
Neural Networks, Deep
Neural Networks, Shallow
Neural Networks - Convolutional Neural Networks (CNN)
Neural Networks - Recurrent Neural Networks (RNN)
Optimization
Principal Component Analysis (PCA) & other dimensionality reduction
Random Forests
Regression
Reinforcement Learning
Statistics - Descriptive
Singular Value Decomposition (SVD)
Support Vector Machine (SVM)
Survival Analysis
Text Mining
Time Series
Uplift Modeling
Visualization
Other Methods
Required
Which of the following best describes your employment type?
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Industry / Self employed
Government / Non-profit
Academia
Student
Other
Which of the following best describes your primary employment region?
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US / Canada
Europe
Asia
Latin America and Mexico
Africa / Middle East
Australia / NZ
Other
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