The power of data analytics
Combining data-intensive best solution (apache spark) and compute-intensive best approach (Tensorflow with GPU) results in Tensorframes. The speedup is remarkable. Hopefully, I could get a multi-GPU cluster to play with. Spark Summit EU talk by Tim Hunter from Spark Summit
Will steep improvement of algorithm + decrease on hardware cost (CPU, memory, disk) drag the distributed approach irrelevant? IMHO, at this time, the winner is h2oai which gives an impressive performance in stand-alone mode and supports distributed platform (i.e., atop Spark using h2o sparkling water). I was so surprised that Standford’s statistics maestro, Tibshirani & … Read moreBattle of ML/DL framework on stand-alone vs. distributed platform
In the last post, I mentioned the Gartner’s magic quadrant as well as the competitive landscape of BI products. KDnuggets covers the data science & ML products in their article (https://bit.ly/2Pococi). Some interesting observations: 1) KNIME & Mathworks increases their completeness of vision in the last 3 years. KDNuggets quotes KNIME “With a wealth of … Read moreData science & ML (commercial) tools: their competitive landscape