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Applied Machine Learning
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BIO397 AML 2021
Julia language
About
Installation
Basics
Parallel computing
Automatic differentiation
Math for ML
Linear Algebra
Calculus
Data handling
Data preparation
Dimensionality reduction
Supervised learning
Linear regression
Ridge and LASSO regressions
Logistic Regression
K-Nearest Neighbors
Decision trees
Random Forests
AdaBoost
Gradient-boosted trees
Naive Bayes
Unsupervised learning
K-means
Mean shift
Anomaly detection
Deep learning
Neural Networks
Convolutional NN
Model validation and evaluation
Validation and evaluation
References
Resources
Combining K-means and mean shift
Combining mean shift and k-means algorithms to cluster non-convex shapes
from https://jamesxli.blogspot.com/2012/03/on-mean-shift-and-k-means-clustering.html
Tags:
clustering
