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Retailers are not the only people looking forward to the holiday season. It will be a busy time for scammers and fraudsters too as they send out coupons, deals and offers to consumers, and even thank-you vouchers to employees, purporting to come from organizations and brands they trust. In fact, CIO has reported that it takes only a few minutes for experienced hackers to set up a social engineering attack against enterprises (and their managed service providers) that consider themselves to be se
This article was published as a part of the Data Science Blogathon. Introduction Most existing research on Twitter spam focuses on account blocking or identifying and blocking spam users or spammers. To detect spam users, we can use traditional machine learning algorithms that use information from users’ tweets, demographics, shared URLs, and social connections as features. […].
Artificial intelligence and machine learning are valuable to data and analytics activities. Our research shows that organizations using AI/ML report gaining competitive advantage, improving customer experiences, responding faster to opportunities and threats and improving the bottom line with increased sales and lower costs. No wonder nearly 9 in 10 (87%) research participants report using AI/ML or planning to do so.
This post is a summary of 2 distinct frameworks for approaching machine learning tasks, followed by a distilled third. Do they differ considerably (or at all) from each other, or from other such processes available?
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When Curt Garner became Chipotle’s first CIO in 2015, the only technology used for online restaurant ordering was, “believe it or not,” a fax machine, he says. Seven years later, the Newport Beach, Calif.-based company is piloting a system with a robotic arm dubbed “Chippy” that prepares the fast-casual chain’s famed fried salt-and-lime chips homemade every day without human labor, with the aim of tailoring output to the daily needs of each restaurant.
This article was published as a part of the Data Science Blogathon. Introduction Biopharmaceutical Industries are the fastest growing industries after considering the basic need for the healthy life of humans and animals. Based on the available literature, the author has identified six major thrust areas of the Biopharmaceutical industry, which has summarized in the […].
Big data is shaping our world in countless ways. Data powers everything we do. Exactly why, the systems have to ensure adequate, accurate and most importantly, consistent data flow between different systems. Pipeline, as it sounds, consists of several activities and tools that are used to move data from one system to another using the same method of data processing and storage.
Big data is shaping our world in countless ways. Data powers everything we do. Exactly why, the systems have to ensure adequate, accurate and most importantly, consistent data flow between different systems. Pipeline, as it sounds, consists of several activities and tools that are used to move data from one system to another using the same method of data processing and storage.
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IT leaders hold a powerful position at Owens Corning. CIO Steve Zerby not only has a seat at the table, but he’s driving business strategy at the manufacturing company thanks to his panoptic view of the centralized yet global organization. He’s able to spot synergies in supply chain processes that could create efficiencies, and connect leaders in high-performing geographies with lower-performing regions that could benefit from their perspective — even if they’re not in the same business division
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Artificial intelligence is driving a number of changes in the financial sector. We pointed out that AI has created new opportunities for investors purchasing real estate stocks. However, it is also creating unique trading opportunities for those using nontraditional investing decisions. One of the ways that smart investors can use AI is with short-selling.
Speaker: Ben Epstein, Stealth Founder & CTO | Tony Karrer, Founder & CTO, Aggregage
When tasked with building a fundamentally new product line with deeper insights than previously achievable for a high-value client, Ben Epstein and his team faced a significant challenge: how to harness LLMs to produce consistent, high-accuracy outputs at scale. In this new session, Ben will share how he and his team engineered a system (based on proven software engineering approaches) that employs reproducible test variations (via temperature 0 and fixed seeds), and enables non-LLM evaluation m
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In 2016, Major League Baseball’s Texas Rangers announced it would build a brand-new state-of-the-art stadium in Arlington, Texas. It wasn’t just a new venue for the team, it was an opportunity to reimagine business operations. The old stadium, which opened in 1992, provided the business operations team with data, but that data came from disparate sources, many of which were not consistently updated.
This article was published as a part of the Data Science Blogathon. Introduction Hey Folks !! In this article, we will discuss implementing a face detector using Haar Cascade in OpenCV python. In the last article, we talked about real-time object classification; if you haven’t checked it yet, the link is here. Identifying a given […]. The post Face Detection using Haar-Cascade using Python appeared first on Analytics Vidhya.
Artificial Intelligence is the new age blessing in disguise, especially when understanding complex data for the company’s benefit. Unfortunately, there have been complaints about AI’s bias. In most cases, the bias manifests as a technical glitch, but it is an oversight by the algorithm feed and society. These ultimately affect what AI portrays depending on who is using the software.
GAP's AI-Driven QA Accelerators revolutionize software testing by automating repetitive tasks and enhancing test coverage. From generating test cases and Cypress code to AI-powered code reviews and detailed defect reports, our platform streamlines QA processes, saving time and resources. Accelerate API testing with Pytest-based cases and boost accuracy while reducing human error.
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This article was published as a part of the Data Science Blogathon. Introduction Niti Ayog, one of the transforming national institutions, has published an article on Blockchain use cases in India. Few questions about Blockchain, why Blockchain, and how we can deploy our applications through the docker and Kubernetes we should know. Objectives We will discuss […].
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