2019 Data Processing Deep Learning Machine Learning 
O'Reilly on Data
FEBRUARY 4, 2019
In a recent survey , we explored how companies were adjusting to the growing importance of machine learning and analytics, while also preparing for the explosion in the number of data sources. As interest in machine learning (ML) and AI grow, organizations are realizing that model building is but one aspect they need to plan for.
O'Reilly on Data
DECEMBER 12, 2019
For all the excitement about machine learning (ML), there are serious impediments to its widespread adoption. Security vulnerabilities : adversarial actors can compromise the confidentiality, integrity, or availability of an ML model or the data associated with the model, creating a host of undesirable outcomes.
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DataKitchen
APRIL 13, 2021
We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . Dagster / ElementL — A data orchestrator for machine learning, analytics, and ETL. . Collaboration and Sharing.
Insight
SEPTEMBER 20, 2019
The model was a modified U-Net and trained on GPU hosted by Amazon Web Services (AWS) EC2 instances. Discussion In this project, I used deep learning techniques to automatically detect lesion regions and classify the lesion, which can have both cost and time-saving benefits. The testing accuracy of the model is 0.79
Cloudera
OCTOBER 1, 2022
Some organizations are choosing to confront these challenges with the help of tools like machine learning (ML) and artificial intelligence (AI) to automate, streamline, and scale compliance. . It is pretty impressive just how much has changed in the enterprise machine learning and AI landscape.
O'Reilly on Data
JANUARY 25, 2021
Year-over-year (YOY) growth compares January through September 2020 with the same months of 2019. Let’s look at the data, starting at the highest level: O’Reilly online learning itself. O’Reilly Online Learning. Usage of O’Reilly online learning grew steadily in 2020, with 24% growth since 2019.
O'Reilly on Data
MARCH 31, 2020
If you’re already a software product manager (PM), you have a head start on becoming a PM for artificial intelligence (AI) or machine learning (ML). But there’s a host of new challenges when it comes to managing AI projects: more unknowns, non-deterministic outcomes, new infrastructures, new processes and new tools.
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