Posts

Showing posts with the label analytics jobs

Featured Post

The Quick and Easy Way to Analyze Numpy Arrays

Image
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

Data science these IT skills you need to learn to get job

Image
The most lucrative analytics skills include MapReduce, Apache Pig, Machine Learning, Apache Hive and Apache Hadoop. Machine learning, big data, and data science skills are the most challenging to recruit for and potentially can create the greatest disruption to ongoing product development and go-to-market strategies if not filled. Image Courtesy|Stockphotos.io Great in demand it skills... Big Data (Information Technology): 3,977% Node.js (Design): 2,493% Tableau (Research and Analysis): 1,581% NoSQL (Information Technology): 1,002% Apache Hadoop (Information Technology): 704% HTML5 (Information Technology): 612% Python (Research and Analysis): 456% Oracle (Sales): 382% JSON (Information Technology): 318% Salesforce CRM (Sales): 292%