Artificial intelligence systems usually learn by example and are likely to learn better with high-quality examples. Low quality or insufficient training data can lead to unreliable systems that make poor decisions, reach the wrong conclusions, introduce or perpetuate bias and cannot handle real-world variation among other issues. Besides, poor data is…

We all experience video streaming issues, probably on a daily basis. But now that people aren’t just streaming for entertainment, but are relying on it in many cases to perform their jobs, it ups the ante to address some of these issues and provide an improved experience. Deep…

Artificial Intelligence (AI) is all the buzz with everyone looking for ways to leverage AI in some capacity within their organization. Whether you’re running a business focused on insurance, construction, or anything in between, the list of companies adding AI or Data Science teams to help their business succeed is growing every day. Unfortunately for…

Artificial intelligence (AI) and machine learning have come a long way, both in terms of adoption across the broader technology landscape and the insurance industry specifically. That said, there is still much more territory to cover, helping…

There are unlimited discussions, and conversations over this well-known point, and it tends to be a touch of overpowering to realize where to begin from data science specialists to finish amateurs.

While, from analysts to students,…

According to global smart learning Industry analysis by Research Dive, the global industry forecast will be $74,179.1 million in 2026, at a 19.2% CAGR and is growing from $18,200.0 million in2018.

Smart Learning industry Drivers: Growing acceptance of e-learning in academic & corporate sectors…

Introduction and Motivation

AI is taking over. In 2021, we’re going to see machine learning taking on a bigger role in data analysis as algorithms become capable of reducing error and producing more accurate models within themselves. These algorithms cover iterative processes, decision trees as well as multi-dimensional splitting of datasets. Machine learning is enabling data analysts to have new and greater insights, affecting everything from marketing departments to the way we learn. Here are the essential machine…

Summary:  Things are getting repetitious and that can be boring.  Still, looking at lessons from the 90s it’s clear there are at least one or two decades of important economic advances that will based on our current AI/ML.  Then some thoughts on where that next really huge breakthrough will come from that will return our initial excitement.

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Summary:  There is now sufficient experience among mid and large sized companies starting their AI journey to identify a single best practice for moving from AI experimentation to scale-up: the AI COE (Center of Excellence).

If you are a mid-sized business, government organization, or educational…

A few years ago, it was extremely uncommon to retrain a machine learning model with new observations systematically. This was mostly because the model retraining tasks were laborious and cumbersome, but machine learning has come a long way in a short time. Things have changed with the adoption of more sophisticated MLOps solutions.

Now, the…

Introduction and Motivation

It is becoming increasingly common for organizations to collect very large amounts of data over time, and to…

Meet two text mining experts in today’s interview, which explores some of the common issues faced by data scientists in text analytics. Prof. Dursun Delen and…

Summary:  Some industries are a clear slam-dunk for AI/ML applications and some less so.  The legal, regulatory, and compliance businesses (law firms, internal legal departments, and the contract review and regulatory compliance departments of heavily regulated industries) fall in this last category.  This is a review of seven companies found by TopBots to be successful; pointing to opportunities others can follow.

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As you must be aware, there are a lot of applications that are a by-product of Machine learning techniques. Machine learning is one of the hottest skills in today’s market. In fact, as per one of the recent LinkedIn surveys, there are over 7k machine learning jobs available. Additionally, there is a tremendous growth rate for machine learning related jobs as well. Another reason which could oblige you to seriously think about this skill set is automation. As we must have heard about…

What is MLOps (briefly)

MLOps is a set of best practices that revolve around making machine learning in production more seamless. The purpose is to bridge the gap between experimentation and production with key principles to make machine learning reproducible, collaborative, and continuous.

MLOps is not dependent on a single technology or platform. However, technologies play a significant role in practical…

Machine Learning is an important skill to have in today’s age. But acquiring the skill set could take some time especially when the path to it is unscattered. The below-mentioned points have a very wider reach to the topics it covers and essentially would give anyone a very good start when it comes to starting from scratch. Learners should not limit…

• Your in-house data science team is not the exclusive source of AI/ML based improvements. 
• Process Re-engineering is gaining new life as a way to optimize data processes.…

Predict Number of Active Cases by Covid-19 Pandemic based on Medical Facilities (Volume of Testing, ICU beds, Ventilators, Isolation Units, etc) using Multi-variate…