A Technology Broker and Management Company Specializing in KM Systems
Favorite Manually inspecting data quality and cleaning data is a painful and time-consuming process that can take a huge chunk of a data scientist’s time on a project. According to a 2020 survey of data scientists conducted by Anaconda, data scientists spend approximately 66% of their time on data preparation and analysis
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Shared by AWS Machine Learning December 13, 2022
Favorite Posted Keerthana Gopalakrishnan and Kanishka Rao, Google Research, Robotics at Google Major recent advances in multiple subfields of machine learning (ML) research, such as computer vision and natural language processing, have been enabled by a shared common approach that leverages large, diverse datasets and expressive models that can absorb
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Shared by Google AI Technology December 13, 2022
Favorite A look at how Transformers are helping robots become more useful. View Original Source (blog.google/technology/ai/) Here.
Favorite Amazon Comprehend is a natural language processing (NLP) service that uses machine learning (ML) to discover insights from text. Amazon Comprehend provides customized features, custom entity recognition, custom classification, and pre-trained APIs such as key phrase extraction, sentiment analysis, entity recognition, and more so you can easily integrate NLP
Read More Shared by AWS Machine Learning December 12, 2022
Favorite Amazon Lookout for Vision provides a machine learning (ML)-based anomaly detection service to identify normal images (i.e., images of objects without defects) vs anomalous images (i.e., images of objects with defects), types of anomalies (e.g., missing piece), and the location of these anomalies. Therefore, Lookout for Vision is popular
Read More Shared by AWS Machine Learning December 12, 2022
Favorite What’s the point of having a KM Policy? Here are 10 arguments in favour. There comes a time when a KM strategy has done its job, and that’s when you need a KM policy. Your Knowledge Management strategy is a strategy for change – a strategy for introducing the
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Shared by Nick Milton December 12, 2022
Favorite Amazon SageMaker Autopilot automatically builds, trains, and tunes the best machine learning (ML) models based on your data, while allowing you to maintain full control and visibility. Autopilot can also deploy trained models to real-time inference endpoints automatically. If you have workloads with spiky or unpredictable traffic patterns that
Read More Shared by AWS Machine Learning December 8, 2022
Favorite In this post, we show how to train, deploy, and predict natural disaster damage with Amazon SageMaker with geospatial capabilities. We use the new SageMaker geospatial capabilities to generate new inference data to test the model. Many government and humanitarian organizations need quick and accurate situational awareness when a
Read More Shared by AWS Machine Learning December 8, 2022
Favorite Across all industries, machine learning (ML) models are getting deeper, workflows are getting more complex, and workloads are operating at larger scales. Significant effort and resources are put into making these models more accurate since this investment directly results in better products and experiences. On the other hand, making
Read More Shared by AWS Machine Learning December 8, 2022
Favorite Data preparation is a principal component of machine learning (ML) pipelines. In fact, it is estimated that data professionals spend about 80 percent of their time on data preparation. In this intensive competitive market, teams want to analyze data and extract more meaningful insights quickly. Customers are adopting more
Read More Shared by AWS Machine Learning December 8, 2022