A great customer experience can differentiate your company in highly competitive markets, as customers become more knowledgeable and demanding. Service agents that provide the correct responses quickly and efficiently both enhance customer experience and also reduce the time the agent spends on the line – lowering operational costs.
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The current implementation of ML algorithms in Spark has several disadvantages associated with the transition from standard Spark SQL types to ML-specific types, a low level of algorithms’ adaptation to distributed computing, a relatively slow speed of adding new algorithms to the current library.
Also, Spark ML doesn’t support online-learning by nature for all algorithms, stacking, boosting and a bunch of approximate ML algorithms that gives a significant speedup in many cases.
But if you choose Ignite ML you could avoid a most of problems mentioned above.
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