With organizations embracing digitization in a big way, the generation of data has grown manifold. According to IDC, the growth of data will be huge across industries, from 16 zettabytes to 160 zettabytes. The data being talked about is useful for businesses to draw insights, formulate strategies, and understand trends and customer behavior, among others. […]
Complete Guide to Image Labeling for Machine Learning
Image labeling enables you to tag and identify specific details in an image. In computer vision, image labeling involves adding specific tags to raw data, including videos and images. Each tag represents a certain object class associated with this data. Supervised machine learning (ML) models utilize labels to learn to identify a certain object class within unclassified […]
Getting to AI Adoption at Scale
Everyone wants to increase the adoption of their AI programs, but there are several “chicken and egg” problems to overcome: How do we get the resources to build out the technical infrastructure required to use AI at scale, when we have not proven the value yet? How do we create a culture of data-driven decision-making […]
SERP-Driven, Dynamic Sentiment Impact Analysis
Sentiment analysis is not entirely new. Businesses have been attempting to generate insights from various pieces of content for some time now. With automated data collection becoming more accessible, sentiment analysis can be done by nearly anyone. While it’s often used by research and development departments for product analysis or by finance institutions to drive […]
Leveraging Enterprise AI
Leveraging enterprise artificial intelligence (AI) provides a system that can automate repetitive tasks, answer questions, and improve decision-making. The AI operates machine learning extensions and automated services to deliver satisfying customer experiences and can streamline research projects. Enterprise AI can be described as a combination of machine learning and deep learning algorithms. With enterprise AI, managers and […]
An Introduction to Reinforcement Learning
In this blog post, I’d like to introduce some basic concepts of reinforcement learning, some important terminology, and a simple use case where I create a game playing AI in my company’s analytics platform. After reading this, I hope you’ll have a better understanding of the usefulness of reinforcement learning, as well as some key […]
The Rise of Data-Centric AI
Data-centric AI is gaining momentum among engineers. While traditionally, a model-centric approach has been used to improve accuracy for a variety of applications, the increase of data available today and the benefits of using reliable data are leading engineers to reevaluate their priorities and workflows. With a model’s performance so dependent on the quality of […]
Machine Learning Tools
Machine learning tools allow computers to become more accurate in predicting outcomes. The computer’s software makes decisions based on experiences rather than programming. The algorithm (basically a series of instructions) collects data on its interactions, and that data is used as feedback for the algorithm, which changes its behavior and responses, improving them over time. […]
How to Make the Jump to AI
AI and machine learning models are being used to help companies stay competitive by discovering new revenue opportunities, improving risk management, detecting fraud, and streamlining business processes. But years ago, data science wasn’t even on the curriculum at universities, so many software engineers are acquiring the necessary skills on their own. From my experience, anyone who […]
Digital Transformation Examples for Business Success
Today, most businesses are embracing digital transformation to meet ever-increasing customer expectations and to remain competitive and relevant in the world economy. While many organizations still struggle to adopt new technologies – often due to the lack of a tailored digital strategy and the reluctance of many to change the way of business operations that […]