Posts by Melody Smith
Machine Learning and Databases
Data sets for machine learning solve big data problems, from data collection and storage through analysis and the training of machine learning models to the deployment of real-time prediction endpoints. VentureBeat brought this interesting information to our attention in their article, “Database technology evolves to combine machine learning and data storage.” This new approach offers…
Read MoreManaging Data
Data has never been more important for organizations to function. More and more data is being created every day and often in formats that make it difficult to use. The more data an organization creates, the more control it needs over it. This interesting topic came to us from The Economic Times in their article,…
Read MoreMachine Learning and Careers
If you are looking to specialize in your career or switch altogether, know that anyone with “machine learning” in their job title or responsibilities, is in a good career place these days. InfoWorld brought this topic to our attention in their article, “Career roadmap: Machine learning engineer.” People with skills and experience in machine learning are in…
Read MoreWhat To Do With The Data?
The responsibility of gathering and integrating data for analytics has typically fallen on data warehouses. They create precision, accuracy and consistency out of messy transactional structures, so that users can look back and make sense of the past. This interesting information came to us from diginomica in their article, “Towards a semantics of data in a…
Read MoreEmerging Technologies in Retail
Technological innovation has always benefited the retail process, both for the customer and retailer. The evolution from manual cash registers to self-service checkout kiosks is just one example. Inventory management software, digital signage and loss prevention technology are a few more. This interesting information came to us from Retail customer Experience in their article, “5…
Read MoreAI in Healthcare
Machine learning has proven itself beneficial in healthcare in numerous ways – predicting disease onset and future hospitalizations, reducing medical errors and managing medications, to name a few. But when bias creeps into the development or use of machine learning models, technologies that intend to improve health outcomes can create barriers for certain patients. This…
Read MoreFighting Fraud with Technology
When you hear about cyberattacks, do you automatically link it to organized crime? Surprisingly, it is very active throughout both the private and public sectors, from banks to federal governments to small businesses. The Crime Report brought this information to us in their article, “A Cyber Weapon to Fight Cyber Fraud: Artificial Intelligence.” According to a…
Read MoreSmart Content
Semantic enrichment is the process of adding a layer of topical metadata to content so that machines can make sense of it and, even more importantly, build connections to it. In the digital world, semantic technologies and procedures automate the classification of digital content and enable the assignment of content to specific topic areas. Semantic methods…
Read MoreThe Value in Data
Organizations often undergo changes due to mergers and acquisitions, joint ventures and system upgrades. These transitions can create silos containing inconsistent and redundant data. Data conversion is a key step in this process that converts raw data into meaningful information. Tech Target brought this interesting information to us in their article, “Improve data value by…
Read MoreMachine Learning Models and Hearing Loss
Hearing loss is rapidly becoming an area of interest and research. The number of baby boomers dealing with hearing loss continues to increase as they age. This interesting news came to us from Science Daily in their article, “Machine learning improves human speech recognition.” Researchers are studying people’s ability to recognize speech to gain a…
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