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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 | 2019-08-22T07:32:52+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 [...]

Know Thy Data – How a Bank Enabled its Global Employees to Discover Information

By | 2019-06-21T13:08:07+00:00 October 4th, 2017|Big Data, Cognitive Services, Concept Tagging, Data Sciences, Emotion Analysis, Entity Extraction, IBM, IBM Watson, IBM Watson Conversation, JSON, Keywords Extraction, Knowledge Management, Machine Learning, Original Content, Predictive Analytics, Predictive Modeling, Relations Extraction, Sentiment Analysis, Taxonomy Classification, Text Analytics|

Data is the most valuable asset for any enterprise today. That’s why knowing what’s where and how to access it in time is super critical for any company’s business success. [...]

Handling Rare Events and Class Imbalance in Predictive Modeling for Machine Failure

By | 2019-03-12T11:17:25+00:00 September 21st, 2017|Analytics, Big Data, Churn, Data Sciences, Hadoop, MapReduce, Marketing Analytics, Pranab Ghosh, Predictive Analytics, Predictive Modeling|

Handling Rare Events and Class Imbalance in Predictive Modeling for Machine Failure Most supervised Machine Learning algorithms face difficulty when there is class imbalance in the training data i.e., amount of data belonging one class [...]

Customer Churn Prediction with SVM using Scikit-Learn

By | 2019-03-12T11:48:24+00:00 April 24th, 2016|Analytics, Big Data, Churn, Data Sciences, Hadoop, MapReduce, Marketing Analytics, Pranab Ghosh, Predictive Analytics, Predictive Modeling|

Customer Churn Prediction with SVM using Scikit-Learn Support Vector Machine (SVM) is unique among the supervised machine learning algorithms in the sense that it focuses on training data points along the separating hyper planes. In [...]

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