I have been reading a book recently about algorithms in the wider sense

(40 algorithms every programmer should know -book and github link below)

I spend a lot of time with algorithms considering my teaching (AI at University of Oxford).

For Machine Learning and Deep Learning, we need to study a…

If you scour the internet for "ANOVA vs Regression", you might be confused by the results. Are they the same? Or aren't they? The answer is that they can be the same procedure, if you set them up to be that way. But there are differences between the two methods. This one picture sums up those differences.

References…

Venn diagram showing overlap between "quantum" and "neural network"

The term "quantum neural networks" is being used with increasing frequency by the quantum computing community. Maybe as a dishonest, bait-and-switch advertising strategy, this makes sense. However, from a scientific standpoint, "quantum neural network" is a very poor name choice for what is being alluded to here.

Artificial Neural Networks, often called "Neural Nets" for short, are supposed to…

I want to share with you my article about marketplaces. If you are interested in creating one or want to improve your existing marketplace you might be interested in this information. I worked with SPD Group experts to give you the latest information on the subject! 

To get the most revenue out of your effort, it is important to pick…

Milvus Project: github.com/milvus-io/milvus

The question answering system is commonly used in the field of natural language processing. It is used to answer questions in the form of natural language and has a wide range of applications. Typical applications include intelligent voice interaction, online customer service,…

Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week. To subscribe, follow this…

It is surprising to see the level of innumeracy in the population, even in college-educated professionals. People still have blind faith in so-called experts and journalists, many experts being innumerate themselves when it comes to reading and interpreting data, even if they are experts in their own field. Here I discuss three examples.…

This article was written by Marcus Oliveira da Silva.

I am not a real data scientist.

I have never used a deep learning framework, like TensorFlow or Keras.

I have never touched a…

Information catalogs and business glossaries are popular solutions in the data management toolbox. What is the purpose of each and how do they work to effectively manage an organization’s data? Which one should you choose as part of your data management strategy?

What’s in a name?

In the world of data management, business glossaries and information catalogs are sometimes discussed as similar entities and considered interchangeable. However,…

This article was written by Bharat Girdhar.

I was always intrigued by the concept of computers taking a decision on behalf of humans. Though the concept of machine learning has been there for decades but…

In my previous article, we analyzed the COVID-19 data of Turkey and selected the cubic model for predicting the spread of disease. In this article, we will show in detail why we selected the cubic model for prediction and see whether our decision was right or not.

When we analyze the regression trend models we should consider overfitting and underfitting…

(This article is now a chapter of my github proto-book Bayesuvius)

Simpson's paradox is a recurring nightmare for all statisticians overseeing a clinical trial for a medicine. It is possible that if they leave out a certain "confounding" variable from a study, the study's conclusion on whether a medicine is effective or not, might be, without measuring that confounding variable, the opposite of what it would have been had that variable been measured. Statisticians have to enlist expert…

Here is our selection of featured articles and technical resources posted since Monday:

Announcements

• Webinar - Humble AI: Building Guardrails Against Overconfidence
• DataOps Optimization: Case Study - Upcomimg Free DSC Webinar

Resources…

Correlation is a measure of linear association between two variables X and Y, while linear regression is a technique to make predictions, using the following model:

Y = a0 + a1 X1 + ...…

Data, an organization’s intellectual asset, must be treated and regularly enriched to remain useful and valuable. Over 80% of companies we’ve worked with, — including Fortune 500 organizations — recorded up to 50% growth in sales and customer satisfaction as one of the many benefits of data enrichment. Those that enriched data in line with a company-wide data management plan recorded a 2X increase in ROI.

In this…

The following graphic is based on Sam Priddy's excellent DSC/Tableau Webinar How to Accelerate and Scale Your Data Science Workflows. Sam covered many interesting points for organizing, analyzing and presenting data--including which graph is best suited for different data types. This graphic is an overview of some of Sam's points. For more…

I just uploaded a new chapter to my github proto-book "Bayesuvius". This chapter deals with Reinforcement Learning (RL) done right, i.e., with Bayesian Networks :)

My chapter is heavily based on the excellent course notes for CS 285 taught at UC Berkeley by Prof. Sergey Levine. All I did was to translate some of those lectures into B net lingo.

During a recent conversation that I had on LinkedIn with some very smart Machine Learning experts, the experts opined that the fields…

 Data scientist ranks third on the list of LinkedIn emerging jobs of 2020. Similarly, it ranks first on Glassdoor’s hottest jobs of 2020. The data scientist role has been consistently ranked among top jobs in the past few years. There’s not a slightest of doubt that data scientists are in huge demand and are expected to stay in high demand in the coming years. …