Favorite When a model gets deployed to a production environment, inference speed matters. Models with fast inference speeds require less resources to run, which translates to cost savings, and applications that consume the models’ predictions benefit from the improved performance. For example, let’s say your website uses a regression model
Favorite Data preparation remains a major challenge in the machine learning (ML) space. Data scientists and engineers need to write queries and code to get data from source data stores, and then write the queries to transform this data, to create features to be used in model development and training.
Favorite The last year has made delivering high-quality customer contact center support extremely challenging. Consumers have increasingly abandoned brick-and-mortar retail shopping and traditional banking in favor of digitally enabled experiences, which brings unprecedented call volumes to contact centers. In many cases, call center staff are also working remotely, which makes
Favorite Domain experts are increasingly using machine learning (ML) to make faster decisions that lead to better customer outcomes across industries including healthcare, financial services, and many more. ML can provide higher accuracy at lower cost, whereas expert oversight can ensure validation and continuous improvement of sensitive applications like disease
Favorite What’s in it for the Knowledge worker, when you introduce Knowledge Management to an organisation? This is a crucial question you need to answer. Luckily it’s an easy one to answer as well. We have already discussed on this blog about the main stakeholder groupings for Knowledge management including the
Favorite With the rapid growth of data, many organizations are finding it difficult to analyze their large datasets to gain insights. As businesses rely more and more on automation algorithms, machine learning (ML) has become a necessity to stay ahead of the competition. Amazon Redshift, a fast, fully managed, widely
Favorite Inventorying store items is a general demand for retail stores and supermarkets. This is usually performed manually by counting items and visually checking the correct placement. Tracking changes in inventory helps business owners evaluate performance of each product, validate correct placement, and set future restocking plans. With the cloud
Favorite Regulatory mandates, audit requirements, and security policies often call for data visibility and granular data control while using Amazon Simple Storage Service (Amazon S3) for shared datasets. Because data on Amazon S3 is often accessible by multiple applications and teams, fine-grained access controls should be implemented to restrict privileged
Favorite DICOM (Digital Imaging and Communications in Medicine) is an image format that contains visualizations of X-Rays and MRIs as well as any associated metadata. DICOM is the standard for medical professionals and healthcare researchers for visualizing and interpreting X-Rays and MRIs. The purpose of this post is to solve
Favorite This post is co-written by Nikunj Agarwal, lead data scientist at Edelweiss Tokio Life Insurance. Edelweiss Tokio Life Insurance Company Ltd is a leading life insurance company in India. Its broad spectrum of offerings includes life insurance, health insurance, retirement policies, wealth enhancement schemes, education funding, and more. How
Shared by AWS Machine Learning June 8, 2021
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