Data rules the world and, as a result, we want data to drive all the big decisions about how the world works because we believe in rationality, evidence, and science. But most organizations struggle to leverage that data to its competitive advantage. It’s probably even accurate to say that, statistically speaking, almost all organizations fail…

Artificial Intelligence is changing how data management and analysis is handled in the age of big data. Organizations are generating more data than ever before and the process of accessing data using traditional methods is not only time consuming but also poses a threat to the data sets. To handle this challenge, AI changes the way we view data in…

A little soup is quickly cooked. But if many chefs are working together on a larger menu that will eventually be appreciated by a banquet of guests, good preparation is key. In this article we will focus on the preparation phase and outline what it means to introduce…

Nowadays, the success of many businesses is primarily attributed to good relationships with their customers. That is, having a comprehensive understanding of what customer needs and availing it to satisfy their needs as well as achieve the business goals.  n Mathematics, 360 degrees is a full rotation that is, there are no blind spots.

Similarly, in…

Network graphs play a large part in both computing and data science, and they are essential for working with (and visualizing) both semantic graphs and property graphs. Nearly thirty years ago, AT&T produced a set of libraries called graphviz which were…

An error correcting code (ECC) is a way of controlling errors in data that is being transmitted over an unreliable or noisy communication channel. In an ECC, the sender encodes the message with redundant information. The receiver is able to detect a limited number of errors, and to correct these errors without retransmission.

Turbo codes are a class of ECC that approach very closely the theoretical…

Introduction to SageMaker

I’ve been working with AWS SageMaker for a while now and have enjoyed great success. Creating and tuning models, architecting pipelines to support both model development and real-time inference, and data lake formation have all been made easier in my opinion.  AWS has proven to be an all encompassing solution for machine learning use cases, both batch and real-time, helping me decrease time to…

That’s correct. 1 server and 10 lines of code are all you need to search among 1 billion images in a few hundred milliseconds. Its ease of use a few lines of code to handle massive-scale reverse image search. Its superior standalone performance satisfies your need for low-latency, real-time searches. Its support for distributed systems and cloud-native…

Brian Huge and I just posted a working paper following six months of…

The challenge with data search

The explosion in unstructured data, such as images, videos, sound records, and text,…

CNN and RNN are amongst most important algorithm of Neural Network family, also they differ in their network process and solving problems.

So talking about their differences:

CNN are used to solve classification and regression problems and RNN are used to solve sequence information.

CNN are used for 2D image…

In supervised machine learning algorithms, Random Forest stands apart as it is arguably the most powerful classification model. When Microsoft developed their X-box game which enables you to play as per the movement of your posture, they used Random Forest over any other machine learning algorithm and over ANN (Advanced Neural Networks) as well !

I am assuming that if you are reading this blog, you are well versed with Decision Tree Classification. However, if you are not, need not…

In my previous post, I introduced the ELAINE Community Tool that can be used to discover variables from textual communications.

Statistical predictors work well for charting the course of economic activities based on macro factors that elicit supply and demand if the market environment is within a close proximity of a pattern that resembles previous economic cycles. Unfortunately, in today’s geo-political environment, many of these new variables are injecting forces that…

Tips

1. Don't try to put the cart before the horse: realize that efficient data preparation (and thus interoperable standards) and data quality, especially in the enterprise environment, are a basic requirement for…

1. Hybrid approach: Semantic AI is the combination of methods derived from symbolic AI and statistical AI. Virtuously playing the AI piano means that for a given use case various stakeholders, not only data scientists, but also process owners or subject matter experts, choose from available methods and tools, and collaboratively develop workflows that are most likely a good fit to tackle the underlying problem. For example, one can combine entity extraction based on…

This article was written by Lance Whitney.

An update to Google's mobile app and website lets you search for symptoms and receive a list of possible conditions and other details. You can now ask Google to help diagnose what ails you.…

Will Artificial Intelligence make subject matter experts obsolete?

Imagine you want to build an application that helps to identify wine and cheese pairings. Who will perform best? Applications solely based on machine learning, those ones which are based on experts' knowledge only, or a combination of both?

Most of the machine learning algorithms were…

These days, many organisations have begun to develop their own knowledge graphs. One reason might be to build a solid basis for various machine learning and cognitive computing efforts. For many of those, it remains still unclear where to start. SKOS offers a simple way to start and opens many doors to extend a knowledge graph over time.

1)…