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The Quick and Easy Way to Analyze Numpy Arrays

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The quickest and easiest way to analyze NumPy arrays is by using the numpy.array() method. This method allows you to quickly and easily analyze the values contained in a numpy array. This method can also be used to find the sum, mean, standard deviation, max, min, and other useful analysis of the value contained within a numpy array. Sum You can find the sum of Numpy arrays using the np.sum() function.  For example:  import numpy as np  a = np.array([1,2,3,4,5])  b = np.array([6,7,8,9,10])  result = np.sum([a,b])  print(result)  # Output will be 55 Mean You can find the mean of a Numpy array using the np.mean() function. This function takes in an array as an argument and returns the mean of all the values in the array.  For example, the mean of a Numpy array of [1,2,3,4,5] would be  result = np.mean([1,2,3,4,5])  print(result)  #Output: 3.0 Standard Deviation To find the standard deviation of a Numpy array, you can use the NumPy std() function. This function takes in an array as a par

Machine Learning The Best Book for Beginners

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You need a mix of different technologies for Data Science projects. Instead of learning many skills, just learn a few. The four main steps of an ML project are extracting the data, model development, artificial intelligence, and presentation. Attending interviews with many skills is not so easy. So keep the skills short. Best Machine Learning Book for Beginners A person with many skills can't perform all the work. You had better learn a few skills like Python, MATLAB, Tableau, and RDBMS. So that you can get a job quickly in the data-science project. Out of Data Science skills, Machine learning is a new concept. Why because you can learn Python, like any other language. Tableau also the same. Here is the area that needs your 60% effort in Machine learning.   Machine Learning The Best Book. Related Posts How to write multiple IF-conditions in Python Simplified