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Favorite Healthcare data can be challenging to work with and AWS customers have been looking for solutions to solve certain business challenges with the help of data and machine learning (ML) techniques. Some of the data is structured, such as birthday, gender, and marital status, but most of the data
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Shared by AWS Machine Learning June 10, 2021
Favorite Amazon SageMaker Studio provides a unified, web-based visual interface where you can perform all machine learning (ML) development steps, making data science teams up to 10 times more productive. Studio gives you complete access, control, and visibility into each step required to build, train, and deploy models. Studio notebooks
Read More Shared by AWS Machine Learning June 9, 2021
Favorite Data generates new value to businesses through insights and building predictive models. However, although data is plentiful, available data scientists are far and few. Despite our attempts in recent years to produce data scientists from academia and elsewhere, we still see a huge shortage that will continue into the
Read More Shared by AWS Machine Learning June 9, 2021
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
Read More Shared by AWS Machine Learning June 8, 2021
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.
Read More Shared by AWS Machine Learning June 8, 2021
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
Read More Shared by AWS Machine Learning June 8, 2021
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
Read More Shared by AWS Machine Learning June 7, 2021
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
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Shared by Nick Milton June 7, 2021
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
Read More Shared by AWS Machine Learning June 4, 2021
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
Read More Shared by AWS Machine Learning June 4, 2021