This looks really useful!
This is a blog containing data related news and information that I find interesting or relevant. Links are given to original sites containing source information for which I can take no responsibility. Any opinion expressed is my own.
Showing posts with label EXPLORATORY DATA ANALYSIS. Show all posts
Showing posts with label EXPLORATORY DATA ANALYSIS. Show all posts
Monday, 19 September 2022
Arabica: A Python Package for Exploratory Analysis of Text Data by Petr Korab via @TDataScience
Arabica provides unigrams, bigrams, and trigrams frequencies by a period in a single line of code. Learn more in this tutorial.
Friday, 12 October 2018
5 Data Science Projects That Will Get You Hired in 2018 by John Sullivan via @kdnuggets
A portfolio of real-world projects is the best way to break into data science. This article highlights the 5 types of projects that will help land you a job and improve your career.
As one of the comments on the article points out these are skills that you need to be able to show. My suggestion is that you use Kaggle to provide a project or at least the data for it., do the things in this as part of a project, and store the code and results on Github so that it can easily be seen.
As one of the comments on the article points out these are skills that you need to be able to show. My suggestion is that you use Kaggle to provide a project or at least the data for it., do the things in this as part of a project, and store the code and results on Github so that it can easily be seen.
Monday, 1 May 2017
The Value of Exploratory Data Analysis by Chloe Mawer via @kdnuggets
In this post, the author will give a high level overview of what exploratory data analysis (EDA) typically entails and then describe three of the major ways EDA is critical to successfully model and interpret its results.
This is crucial and it's important that it is done properly.
This is crucial and it's important that it is done properly.
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