JUNE 26, 2023
We use Amazon Neptune to visualize the customer data before and after the merge and harmonization. Overview of solution In this post, we go through the various steps to apply ML-based fuzzy matching to harmonize customer data across two different datasets for auto and property insurance.
AWS Machine Learning Blog
MARCH 15, 2024
Additionally, healthcare datasets often contain complex and heterogeneous data types, making data standardization and interoperability a challenge in FL settings. Because this data is across organizations, we use federated learning to collate the findings. He entered the big data space in 2013 and continues to explore that area.
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IBM Journey to AI blog
SEPTEMBER 5, 2024
Value realization Good data governance aims to maximize the value of data as a strategic asset, enhancing decision-making, big data analytics , machine learning and artificial intelligence projects. Auto-generated audit logs : Record data interactions to understand how employees use data.
AWS Machine Learning Blog
MAY 3, 2023
But from an ML standpoint, both can be construed as binary classification models, and therefore could share many common steps from an ML workflow perspective, including model tuning and training, evaluation, interpretability, deployment, and inference. The final outcome is an auto scaling, robust, and dynamically monitored solution.
AWS Machine Learning Blog
JUNE 3, 2024
Complete the following steps: Choose Run Data quality and insights report. For Problem type , select Classification. For Data size , choose Sampled dataset. In the following example, we drop the columns Timestamp, Country, state, and comments, because these features will have least impact for classification of our model.
ODSC - Open Data Science
APRIL 17, 2023
One significant advantage of H2O AutoML is its ability to handle large data sets with relative ease and its ability to scale horizontally across multiple machines, making it a perfect fit for projects working with big data. Auto-ViML : Like PyCaret, Auto-ViML is an open-source machine learning library in Python.
The MLOps Blog
JUNE 27, 2023
Databricks Databricks is a cloud-native platform for big data processing, machine learning, and analytics built using the Data Lakehouse architecture. Some of its features include a data labeling workforce, annotation workflows, active learning and auto-labeling, scalability and infrastructure, and so on.
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