Wait, the AI advantage is already here and gone? 

That’s what Deloitte warns in their report “Future in the balance? How countries are pursuing an AI advantage”.A noteworthy quote:

“There are indications that the window for competitive differentiation with AI is rapidly closing. As AI technologies become easier to consume and get embedded in…

Our model for recognizing specific animals in images is a neural network consisting of multiple layers, and the initial layers are already good at understanding the world in general. So instead of “re-inventing the wheel,” we only need to train the final layers.

I was excited to work on a recent project with one of our partners, Wild Detect, because it aligns with one of our goals at Appsilon — to use data science consulting to aid in the…

Whether we know it or not, we use Natural Language Processing every day. It makes it easier for us to interact with computers and software and allows us to perform complex searches and tasks without the help of a programmer, developer or analyst.

In this, the last article in our three-article series we discuss Natural Language Processing and…

Data is growing at an unimaginable speed. Data has been and will be the most crucial driving factors behind day-to-day activities that we carry out. As we talk, tons and tons of data---in exabytes is being added and processed each day, making it difficult to handle such an astronomical amount. There lies one major difficulty in handling such large amount of data. Since the volume is increasing rapidly in comparison to the computing resources, we find it…

I recently downloaded a 5 year Public Use Microsample (PUMS) from the latest release of the American Community Survey (ACS) census data. The data contain a wealth of demographic information on both American households and…

Summary:  Business doesn’t want AI.  Business wants results.  While we were focused inward on our Advanced Analytic Platforms, smart competitors were rolling up AI/ML with other capabilities into “Intelligent Automation” platforms.  This large scale integration of capabilities of which AI/ML is only a part looks a lot like the development of ERPs in the late 90s.

 …

The Catch 22 problem holding back AI application adoption  ...

Last week, there was an interesting report in the MIT technology review that Artificial Intelligence can help construction industry to help see…

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…

This book is intended for busy professionals working with data of any kind: engineers, BI analysts, statisticians, operations research, AI and machine learning professionals, economists, data scientists, biologists, and quants, ranging from beginners to executives. In about 300 pages and 28 chapters it covers many new topics, offering a fresh perspective on the subject, including rules of thumb and recipes that are easy to automate or integrate in black-box systems, as well as new…

I am delighted to present my new blog - AI Business Transformation Playbook for Executives. originally posted here. I get into the nuts-and-bolts of AI Systems Solutioning in this rather lengthy blog but the “First Ten Plays” at the end summarizes the key steps. I look forward to your thoughts and…

Our client was a pioneering company in producing and delivering Roof Shingles. Their main plant in Minnesota and they have around 25 more plants across US. Client implemented 100’s of sensors along the assembly line that are streaming nano-second data to their Spark Data-lake.

Viscosity of input fluid is an important factor to maintain quality of production of roof shingles. Data shows there are unwanted peaks (outliers) in viscosity data which client wanted to eliminate. Following…

Bayesian Machine Learning (part - 1)

Introduction

As a data scientist, I am curious about knowing different analytical processes from a probabilistic point of view.  There are two most popular ways…

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

Resources:

• The Divergence Index: A new polarization measure for ordinal categorical variables
• Comparing…

This article broadly describes the capabilities that constitute an enterprise analytics program or competency. The intention initially, was to provide tips on mitigating challenges encountered in implementing an analytics practice - but that is going to be relegated to a future article.

IT projects in general, and analytics projects, in particular, are notoriously unsuccessful or "challenged". 

Focusing attention on the following short list prior to embarking on an analytics…

In the beauty industry, chatbots are seen to solve much more than tangible problems. During the initial phase, its usage was straightforward and cautious - Personalized communication, 24/7 availability, product inquiry, and reaching the target audience.

But as the beauty world is much more personalized than any other industry, the big brands started leveraging chatbot in a lot more personal aspects.

1. Personalized…

Machine Learning has seen a tremendous rise in the last decade, and one of its sub-fields which has contributed largely to its growth is Deep Learning. The large volumes of data and the huge computation power that modern system possess has given Data Scientist, Machine Learning Engineers, and others to achieve ground-breaking results in the Deep Learning and continue to bring in new developments in this field.

In this blog post, we would cover the deep learning data sets that you…

How product managers can learn what they need to know about AI to be at peak effectiveness

The most frequent question I get about AI from colleagues, product managers and others, is,

"What do I need to know about AI and what's the best way to learn it?"

I've invested a considerable amount of time taking…

In an earlier description of clustering algorithms we described an algorithm by which locally optimum partitions and center of gravity of multi-dimensional vectors/points may be obtained. If only one or two dimensional data are considered the optimum partitioning to obtain the so-called Voronoi regions are known. For one-dimension it is the interval while for two-dimensions it is hexagon (think of honey-bee nests or cellular…

A myriad of options exist for classification. In general, there isn't a single "best" option for every situation. That said, three popular classification methods— Decision Trees, k-NN & Naive Bayes—can be tweaked for practically every situation.

Overview

Naive Bayes and K-NN, are both examples of supervised learning (where the data comes already…