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Recurrent Neural Networks cheatsheet

By | 2019-01-08T05:16:21+00:00 January 8th, 2019|Data Sciences|

Recurrent Neural Networks cheatsheet By Afshine Amidi and Shervine Amidi Overview Architecture of a traditional RNN ― Recurrent neural networks, also known as RNNs, are a class of neural networks that allow previous outputs to be used as [...]

Outlier Detection using Apache Spark Solution

By | 2019-01-02T11:57:19+00:00 November 6th, 2018|Analytics, Artificial Intelligence, Big Data, Big Data Technologies, Data Sciences, Machine Learning, Original Content, Predictive Analytics, Predictive Modeling, Recommendations|

Outlier Detection using Apache Spark Solution Sometimes an outlier is defined with respect to a context. Whether a data point should be labeled as an outlier depends on the associated context. For a bank [...]

Harnessing Machine Learning for Anomaly Detections in Web Server Logs

By | 2018-12-06T11:51:22+00:00 November 4th, 2018|Analytics, Artificial Intelligence, Azure, Cognitive Services, Data Sciences, Deep Learning, Featured, Machine Learning, Microsoft Azure, Original Content, Predictive Analytics, Predictive Modeling|

Detecting Anomaly in Web Server Logs with Microsoft Azure Cloud – For FREE and at one-tenth the effort! Every website has web server logs which record the intricate details of site visitors – their [...]

Auto Training and Parameter Tuning for a ScikitLearn based Model for Leads Conversion Prediction

By | 2019-01-04T07:38:28+00:00 May 29th, 2018|Analytics, Blogs, Data Sciences, Pranab Ghosh, Predictive Analytics, Predictive Modeling, Python, ScikitLearn|

Auto Training and Parameter Tuning for a ScikitLearn based Model for Leads Conversion Prediction This is a sequel to my last blog on CRM leads conversion prediction using Gradient Boosted Trees as implemented in ScikitLearn. The focus of [...]

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