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…

Importance of C++ in Data Science and Big Data

Introduction and Motivation – Why C++

C++ is ideal for dynamic load balancing, adaptive…

Summary:  The annual Burtch Works salary survey with data through April shows that opportunities and salaries are still excellent for both new and experienced data scientists.  They also offer some anecdotal observations about the impact of the first few months of COVID on our work and opportunities.

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AI for People and Business is an AI book and AI strategy framework. Here's the official book trailer where I explain important topics that are covered in the book, as well as the beneficial aspects of reading it and the importance of developing a strong AI strategy.

FREE CHAPTER DOWNLOAD -…

Summary:  Transfer Learning (TL) may be the most important aid to adoption of deep learning in the last several years.  This new LEEP measure predicts the accuracy of the transfer and should make TL faster, cheaper, and better.

What is the single most important innovation in deep learning in the last several…

Machine learning is tied in with creating predictive models from uncertain data. Uncertainty implies working with imperfect or fragmented information.

In any case, we can oversee uncertainty utilizing the tools of probability.…

In the past few years, Machine Learning has rapidly changed our lives with its efficient applications. Thi technology has given an uplift to the entire mobile industry. Making devices and mobile apps as intelligent as humans, machine learning is…

Summary:  Less than 9%?  What this study really shows and what we should take away from it.

Wow.  Less than 9%!  Can this be true?  Well according to a large scale survey study conducted by the US Census Bureau it’s actually a…

If you were to invest in real estate, what would be the most important factor you’d take into account? Would it be the age of the building, its location, or maybe how many owners it previously had?

While all of the above will certainly be important to you (though to varying extents), there’s one universal factor that will either be a deal-breaker or make you want to go all in.

You’ve guessed it — the price.

We all have a rough overview of…

Dropout means to drop out units which are covered up and noticeable in a neural network. Dropout is a staggeringly in vogue method to overcome overfitting in neural networks.

Deep Learning framework is now getting further and more profound. With these bigger networks, we can accomplish better prediction exactness. However, this was not the case a few years ago. Deep…

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 and correcting the bias presents difficult issues for data scientists that need to be carefully thought through before reaching conclusions.

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