Итоги

https://www.coursera.org/course/ml

Что ж, давайте поглядим, сколько материала в этом блоге получилось по итогам курса Machine Learning.

Linear Regression

http://vasnake.blogspot.com/2014/05/linear-regression.html

Logistic Regression

http://vasnake.blogspot.com/2014/05/logistic-regression.html

Neural Networks, forward/back propagation

http://vasnake.blogspot.com/2014/05/neural-networks.html

Advice for Applying Machine Learning: algorithm evaluation, metrics, high bias/high variance — суть underfitting/overfitting, learning curves

http://vasnake.blogspot.com/2014/05/advice-for-applying-machine-learning.html

Support Vector Machines (SVMs), Large Margin Classificators, Kernels

http://vasnake.blogspot.com/2014/06/svm-kernels.html

Clustering (K-Means)

http://vasnake.blogspot.com/2014/06/k-means.html

Dimensionality Reduction, Principal Component Analysis (PCA)

http://vasnake.blogspot.com/2014/06/pca.html

Anomaly Detection, Multivariate Gaussian Distribution

http://vasnake.blogspot.com/2014/07/anomaly-detection-recommender-systems.html

Recommender Systems, Content-based recommender systems, Collaborative filtering

http://vasnake.blogspot.com/2014/07/recommender-systems.html

Large-scale Machine Learning, Stochastic Gradient Descent, Mini-batch Gradient Descent; Online Learning

http://vasnake.blogspot.com/2014/07/large-scale-machine-learning-example.html

Map-Reduce and data parallelizm

http://vasnake.blogspot.com/2014/08/large-scale-machine-learning-example.html

Photo OCR example application, pipeline, sliding window

http://vasnake.blogspot.com/2014/08/machine-learning-example-application.html

Getting lots of data; Ceiling Analysis

http://vasnake.blogspot.com/2014/08/getting-lots-of-data-and-artificial-data.html

И ведь это только начало. Поверхностный взгляд показывает огромное количество неохваченного курсом материала.

original post http://vasnake.blogspot.com/2014/08/blog-post.html