Auto-classification Explainability Software Development 
AWS Machine Learning Blog
NOVEMBER 14, 2024
Transparency and explainability : Making sure that AI systems are transparent, explainable, and accountable. However, explaining why that decision was made requires next-level detailed reports from each affected model component of that AI system. Mitigation strategies : Implementing measures to minimize or eliminate risks.
AWS Machine Learning Blog
APRIL 8, 2024
This version offers support for new models (including Mixture of Experts), performance and usability improvements across inference backends, as well as new generation details for increased control and prediction explainability (such as reason for generation completion and token level log probabilities).
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
AWS Machine Learning Blog
JULY 31, 2023
In this post, we show how a business analyst can evaluate and understand a classification churn model created with SageMaker Canvas using the Advanced metrics tab. We explain the metrics and show techniques to deal with data to obtain better model performance.
AWS Machine Learning Blog
OCTOBER 8, 2024
In this blog post, we explore a comprehensive approach to time series forecasting using the Amazon SageMaker AutoMLV2 Software Development Kit (SDK). We’ll walk through the data preparation process, explain the configuration of the time series forecasting model, detail the inference process, and highlight key aspects of the project.
Snorkel AI
FEBRUARY 27, 2023
His presentation explained data-centric AI’s promise for overcoming what is increasingly the biggest bottleneck to AI and machine learning: the lack of sufficiently large, labeled datasets. This is a platform that supports this new data-centric development loop. This could be something really simple.
Snorkel AI
FEBRUARY 27, 2023
His presentation explained data-centric AI’s promise for overcoming what is increasingly the biggest bottleneck to AI and machine learning: the lack of sufficiently large, labeled datasets. This is a platform that supports this new data-centric development loop. This could be something really simple.
The MLOps Blog
FEBRUARY 27, 2023
Michal, to warm you up for all this question-answering, how would you explain to us managing computer vision projects in one minute? Michal: As I explained at some point to me, I wouldn’t say it’s much more complex. What’s your approach to different modalities of classification detection and segmentation?
Expert insights. Personalized for you.
89 
Let's personalize your content