Quick links

What has caught my attention lately:

• Dimensionality reduction techniques : "sparse random projections". ... "Again, random projections are not suitable for all datasets. There is no 'silver bullet' approach to dimensionality reduction." ([1] [2])
• "Ten Lessons Learned from Building (real-life impactful) Machine Learning Systems" ([3])
• NLP tool list. ([4] [5](can't open now...) )
• "Optimizing Python in the Real World" ([6])
• HBase v1.0! ([7])
• Data Science At Zillow ([8])
• "The G-means algorithm takes a hierarchical approach to detecting the number of clusters." ([9] [10])
• Comparing supervised learning algorithms ([11])