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020			_a 9789363861817
082			_a006.312 BOW
100			_aBowles, Michael
245			_aMachine learning with Spark and Python: essential techniques for predictive analytics
250			_a2nd ed.
260			_aNew Delhi: _bWiley India, _c2025.
300			_axxix, 364p.: _bpbk.: _c24 cm.
504			_aIncludes Appendices and Index.
520			_aMachine Learning with Spark and Python Essential Techniques for Predictive Analytics, Second Edition simplifies ML for practical uses by focusing on two key algorithms. This new second edition improves with the addition of Spark—a ML framework from the Apache foundation. By implementing Spark, machine learning students can easily process much large data sets and call the spark algorithms using ordinary Python code. Machine Learning with Spark and Python focuses on two algorithm families (linear methods and ensemble methods) that effectively predict outcomes. This type of problem covers many use cases such as what ad to place on a web page, predicting prices in securities markets, or detecting credit card fraud. The focus on two families gives enough room for full descriptions of the mechanisms at work in the algorithms. Then the code examples serve to illustrate the workings of the machinery with specific hackable code. https://www.wiley.com/en-be/Machine+Learning+with+Spark+and+Python%3A+Essential+Techniques+for+Predictive+Analytics%2C+2nd+Edition-p-9781119561934
650			_aMachine Learning
650			_aPredictive Analytics
650			_aSpark
650			_aPython
650			_aAlgorithm
942			_cTD _2ddc
999			_c63053 _d63053