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

Resources

• Accelerated AI and Advanced Graphics to Accelerate Multiple Workloads
• Traditional vs Deep Learning Algorithms in the Telecom Industry…

I can't find anymore where this chart, featuring relations between distributions, was first published. I remember seeing it on the Cloudera blog.

Another shorter one featuring the most useful one for statistical analysis, can be found…

In the era of the Internet, the ability to crunch large amounts of data and process it with speed and efficiency has become essential for businesses to survive. But you try sitting down and going through all that data by hand: you'll get done sometime in the year 2050 if you're lucky.

That's where machine learning comes to the rescue. But…

Earlier this week, I was speaking at an event on AI for Real Estate where I showed an example from a BBC clip which said that “central London is now a ghost town” (due to COVID 19)

A few months ago, this headline would have been laughable

In London, central London and the London underground are a key fabric of daily…

Mike Romeri, CEO

Analytics2Go

During the current COVID-19 pandemic, virtually all companies have faced significant changes in demand.  Some companies have seen significant increases (e.g., grocery chains, packaged food companies), and others have seen their revenue drop to unsustainable levels (e.g., air travel, hospitality, automotive). Still others have seen both outcomes if they serve different industry segments with very different levels of end-user demand.

While the…

Overview:

This post is about improving the effectiveness of the data science team and improving collaboration between data scientists and stakeholders for better outcomes.  

Aligning goals:

Regardless of the specific project, agreeing on the expected outcomes and goals before beginning the work is a best practice. But with the advent of machine learning (ML) models, it’s for both sides to discuss the critical measures of success for the…

Overview:

As a data scientist, have you ever been frustrated that your stakeholders don’t see the value that you bring to the table? You may ask yourself, “How far should I go in explaining the work I do or what my models are doing?” If that sounds like you, then pay close attention to this post and the next, as they are all about improving collaboration between data scientists and other stakeholders. 

This is a two-part post: This article…

Summary:  Advances in very low cost compute and Model Based Reinforcement Learning make this modeling technique that much closer to adoption in the practical world.

We keep asking if this is the year for reinforcement learning (RL) to finally make good on its many promises.  Like flying cars and jet packs the…

Over the last couple of years, there has been a lot of hype around robotic process automation. This makes a lot of sense if you consider that in 2018 Gartner was already labeling it “…

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…

Time Series forecasting in PBI is based on the thumb technique of smoothening time series prediction called Exponential Smoothening (ES). ES of time series data assigns exponentially decreasing weights for newest to oldest observations. ES is also be used for time series with trend and seasonality. This model is usually used to make short term forecasts, as longer-term forecasts using this technique can be quite unreliable. Collectively, the methods are sometimes referred to as ETS models,…

Blockchain technology is the talk of the techno-world. The technology is booming at a faster rate and is promising for almost all industries as it conforms trust relations in the techno-world. Blockchain builds a trusted network through its encryption algorithms and accounts for controllable permissions, provenance, transactions, smart contracts, and many applications.…

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

Resources

• How to approach the study of algorithms?
• ANOVA vs Regression in One Picture…

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,…