APACHE SPARK MACHINE LEARNING FOR CTR PREDICTION
Click prediction algorithms are essential & used extensively for sponsored search and real-time ad bidding. The current advertising scenario often makes the predictions redundant, if they are not near real-time.
In this webinar, we explain the application of Spark’s machine learning pipeline for predicting Click Through Rates (CTRs). We also cover the many challenges you may face & how to overcome them.
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Chief Revenue Officer
Priding himself on execution excellence, Suresh drives Imaginea’s business growth through robust sales, marketing & business strategies. In a career spanning twenty years, he has had senior leadership roles, driving business growth for Hitachi Consulting/Sierra Atlantic, SoftSol, CSS Corp, and HP/Compaq. He is a proven leader with a successful track record, known for his ability to build high performance teams and drive profitability and growth.
Head – Data Analytics
An alumnus of IIT Guwahati with over ten years of industry experience, Sachin spearheads the data engineering and analytics practice at Imaginea. He combines data science and data engineering expertise to solve complex problems in big data and machine learning. Sachin has been pivotal in implementing Apache Spark solutions for several FAST 5000 companies in predictive recommendation, anomaly detection & contextual Search.