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Good knowledge of various machine learning and deeplearning algorithms will be a bonus. Knowledge of popular big data tools like Apache Spark, Apache Hadoop, etc. Thus, having worked on projects that use tools like Apache Spark, Apache Hadoop, Apache Hive, etc.,
It is much faster than other analytic workload tools like Hadoop. Apart from data analysis, it can also help in machine learning projects. It caters to various built-in Machine Learning APIs that allow machine learning engineers and data scientists to create predictive models. It also supports visualization features.
Google launched its Cloud Platform in 2008, six years after Amazon Web Services launched in 2002. Tensorflow: Tensorflow is an already renowned name in the machine learning community. It is used widely in deeplearning models and packs many useful Machine Learning functions.
Amazon Web Services was launched in July 2002 from the existing Amazon cloud platform with the initial purpose of managing online retail transactions. Ace your Big Data engineer interview by working on unique end-to-end solved Big Data Projects using Hadoop. Also, you shall focus on capacity optimization for allocation.
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