Digital Storytelling for Data, AI, B2B & SaaS | Content in Picsellia, Yellowfin, V2 Cloud, Cognizer, Atlan, Restack, Idera | Patent for Hazen.ai | MS Data Science
What benefits does AI hold for radiologists? Can machines be trusted to make critical healthcare decisions? Learn all that AI offers for radiology and what the future looks like.
This article will discuss the importance of data loss prevention in the GenAI ecosystem, how modern solutions cater to GenAI problems, and mention some best practices for implementing a DLP infrastructure optimally.
LangChain is an open-source framework that facilitates the construction of LLM-based applications. It hosts various open-source and paid models, including fine-tuning and model integration features.
It also supports easy experimentation logging with Comet using the Callback Handler. Comet automatically logs all experiment metrics and inputs and outputs received. It also compiles various experiments under a single project for easy comparison.
Kullback-Leibler (KL) divergence, or relative entropy, is a metric used to compare two data distributions. It is a concept of information theory that contrasts the information contained in two probability distributions. It has various practical use cases in data science, including assessing dataset and model drift, information retrieval for generative models, and reinforcement learning.
This article is an intro to KL divergence, its mathematics, how it benefits machine learning practitioners,...
A graph data structure extracts knowledge from various sources, creates connections between entities, and forms an entwined net called the ‘Knowledge graph.’ A common source of information for knowledge graphs is text. The text to graph approach builds a representation of the knowledge and provides a birds-eye view of the entire corpus.
In computer vision (CV), high-quality training data does not ensure high-performing production models. The real work begins after production deployment when the model’s performance starts deteriorating due to multiple factors that we’ll discuss in this article.
Operationalizing data means using the data from repositories like data warehouses to add business value - and two popular solutions enable it — reverse ETL tools and customer data platforms (CDP).
Reverse ETL is a data integration process that pulls data from data warehouses or lakes into business applications. Meanwhile, a customer data platform (CDP) is a platform that merges customer data from various sources.
As products, Reverse ETL tools and CDPs are not mutually exclusive. So, reverse ...
"But it was running on my machine!". Every developer has said this in his/her life while shipping his/her app to a friend or an app tester. Now you would say: “It just takes some minutes to install the dependencies and configure it to run it on another system, it’s okay, I can handle it”. But, it’s not about me or you. Tech giants with hundreds and thousands of users cannot bear a downtime of even a millisecond. Similarly, collaboration in large teams is not even possible if you cannot sim...
As organizations aim to gain timely insights from large volumes of real-time data, they should ensure that their data ingestion and integration pipelines run seamlessly.
However, the two data terminologies are often used interchangeably, leading to queries, such as “data ingestion vs. data integration” and “are data ingestion and data integration the same?”.
This article will settle the data ingestion vs. data integration debate by highlighting their interrelationships and differences.
Deciding to go for an all-in-one solution like Citrix or a simple VPN mainly boils down to your business requirements.
The first step is taking a deep dive to understand your business’s internal requirements and pain points. Next, you’ll have to understand the difference between both. This will help you decide whether your business needs a VPN or it needs something with advanced features such as Citrix.
You had a groundbreaking idea for a machine learning (ML) project and found a great dataset online. You train this data using state-of-the-art ML techniques and produce promising results in your first run.
But something seems off.
Your model seems to struggle when you deploy it in production. When faced with real-world data, the performance is not what you expected.
Problems arise when your data is insufficient, and your model cannot extract adequate information. Moreover, many open-source da...
The decision to migrate your IT infrastructure to the cloud is the first step toward optimizing internal resources. It’s a long process, but it’s worthwhile once you go through it. However, two different things are simply deciding to migrate vs. doing it.
The market for public cloud services has been on a steady rise. Google’s Cloud service is no stranger to this rise, with Google Cloud’s share of Alphabet’s overall revenue growing from 4.3% in 2018 to 7.5% in 2021. The product/service offeri...
The emergence of Desktop-as-a-Service (DaaS) platforms such as Amazon Workspace has proven highly beneficial in cost reduction. Especially for SMBs, such platforms help in scaling the business more efficiently, as companies only pay for infrastructure as much as is required at any given moment.
However, choosing the ‘pay-as-you-go’ model with Amazon Workspace can sometimes prove to be counterintuitive, as the charges based on your usage can add up to be a hefty sum. This is because when you ‘...