This is a new series, featuring great content from our top contributors. Some of these articles are rather technical in nature, but many are business-oriented and written in simple English. The entire series consists of about 120 articles. We intend to publish a new set every two weeks or so. Click here to check out the previous edition. To read more articles from a same author, read one of his/her articles and click on his/her profile picture to access the full list. Some of these articles are curated or posted as guest blogs.
Selected Recent Articles from Top DSC Contributors
* How to Lie with Data – By Karolis Urbonas
* AI vs Deep Learning vs Machine Learning – By Bill Vorhies
* Naive Bayes Classification explained with Python code – By Ahmet Taspinar +
* How To Implement ML Algorithm Performance Metrics From Scratch With Python – By Jason Brownlee
* Building a Deep Learning Model for Process Optimisation – By Sankaran Iyer
* Making data science accessible – Markov Chains – By Kevin Chisholm
* How To Interpret R-squared and Goodness-of-Fit in Regression Analysis – By Jim Frost
* An example machine learning notebook – By Randal S. Olson
* How to create a Twitter Sentiment Analysis using R and Shiny – By Diego Lescano
* From DevOps to DataOps – By Andy Palmer
* 8 Types of Data – By Bob Hayes
* xda: R package for exploratory data analysis (plotting, univariate, bivariate) – By Ujjwal Karn
* More data beats better algorithms – By Tyler Schnoebelen – By Tyler Schnoebelen
* Data Scientist Core Skills – By Mitchell A. Sanders
* Implementing the Gradient Descent Algorithm in R – By S. Richter-Walsh
* Making data science accessible – Logistic Regression – By David Robinson
* 10 Common NLP Terms Explained for the Text Analysis Novice – By Mike Waldron
Source for picture: article flagged with a +
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