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Showing posts from June, 2019

Numpy Tutorial - Numpy Tutorial Python - Numpy Tutorial For Beginners | asingleneuron

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Let's start our journey with numpy. NUMPY is a python library, capable of doing array processing with an ease. Numpy is capable of performing any kind of array operation with a lightening speed. This is much needed tool to accomplish day to day task which requires multi-dimensional array.  Numpy is also useful for linear algebra.  As a data scientist we daily deal with arrays :) In this journey we will see useful function what makes you day to day task easy. Prerequisite : you should be familiar with Python. KAGGLE KERNEL used to generate this blog post. 

Ericsson ML Challenge Winning Solution | asingleneuron

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Ericsson ML Challenge was focused on NLP and Predictive Analytics problem.  This was a two round challenge. First round was online round, top participants from first round called for offline round at Ericsson office to present their approach and thought process to solve these problems to the Jury.   I won the hackathon by securing 2nd place after the offline round. Problem Statement 1: PREDICT MATERIAL TYPE Assume that you are a member of a marketing agency and you are given a dataset having the title, subjects, and other features, based on which you have to predict what will be the material of to-be-published research so that you can tie-up with an ideal publisher and help them grow.  TRAINING DATA contains 31653 rows  and 12 features TEST DATA contains 21102 rows and 11 features  The following are the material types: Book Sound disc Videocassette Sound cassette Music Mixed CR This is a multi-class classification problem, we are havin