Data As Commodity: For Data Science Professional
What is a commodity? Commodity are basic raw materials with certain standards that are used with other goods, commodity are often the basis of the production of various f...
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Data Governance: Bottom Up Approach to break silos
Over a period, large organizations have been transformed into disintegrated silos that has grown to be a major impediment to respond to changing market demands with agili...
The Rise and Rise of Price Analytics!
Recently Netflix launched Rs 199 ($2.8) mobile-only monthly plan in India. CyberMedia Research (CMR) reported that after the release of the new mobile plan, Netflix now h...
Common Errors in Machine Learning due to Poor Statistics Knowledge
Probably the worst error is thinking there is a correlation when that correlation is purely artificial. Take a data set with 100,000 variables, say with 10 observations. ...
IoT in Agriculture: A Bonus for All your Farming Activities
How great would it be to monitor your fields remotely through a smart gadget? The Internet of Things is defining the new present and future of the farming world. It is po...
DSC Webinar Series: Productive, Self-Service Data Science
Data science is a core part of an organization’s digital transformation strategy. The algorithms the data science team creates are key to reducing the amount of time ...
23 sources of data bias for #machinelearning and #deeplearning
In the paper A survey on bias and fairness in machine learning.- the authors outline 23 types of bias in data for machinelearning. The source is good – so below is an...
Adding Uncertainty to Deep Learning
This article was written by Motoki Wu. Full title: How to construct prediction intervals for deep learning models using Edward and TensorFlow. Edward and Tensorflow. Sou...
Math vs. Statistics in One Picture
Math and statistics are vital components of any data scientist’s tool box. While some view statistics as a type of math, the reality is that they are completely dif...
Racial Bias in Modeling – Not as Simple as You Might Think
Summary: Bias in modeling has long been a public concern that is now amplified and focused on the disparate treatment models may cause for African Americans. Defining...