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Deep Learning Approaches in Medical Image Segmentation

KDnuggets

Medical imaging has been revolutionized by the adoption of deep learning techniques. The use of this branch of machine learning has ushered in a new era of precision and efficiency in medical image segmentation, a central analytical process in modern healthcare diagnostics and treatment planning.

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Types of Bias in Machine Learning

KDnuggets

business, security, medical, education etc.). The sample data used for training has to be as close a representation of the real scenario as possible. There are many factors that can bias a sample from the beginning and those reasons differ from each domain (i.e.

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Understanding Cancer using Machine Learning

KDnuggets

Use of Machine Learning (ML) in Medicine is becoming more and more important. One application example can be Cancer Detection and Analysis.

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How to get datasets for Machine Learning?

Knowledge Hut

Datasets play a crucial role and are at the heart of all Machine Learning models. Machine Learning without data sets will not exist because ML depends on data sets to bring out relevant insights and solve real-world problems. Quality data is therefore important to ensure the efficacy of a machine learning model.

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Pattern Recognition in Machine Learning [Basics & Examples]

Knowledge Hut

Pattern recognition is used in a wide variety of applications, including Image processing, Speech recognition, Biometrics, Medical diagnosis, and Fraud detection. To build a strong foundation and to stay updated on the concepts of Pattern recognition you can enroll in the Machine Learning course that would keep you ahead of the crowd.

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Scalable Model Development and Production in Snowflake ML

Snowflake

In 2024, we launched over 200 AI features, including a full suite of end-to-end ML features in Snowflake ML , our integrated set of capabilities for machine learning model development, inference and operationalization. CHG builds and productionizes its end-to-end ML models in Snowflake ML.

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Audio Analysis With Machine Learning: Building AI-Fueled Sound Detection App

AltexSoft

Today, we have AI and machine learning to extract insights, inaudible to human beings, from speech, voices, snoring, music, industrial and traffic noise, and other types of acoustic signals. At the same time, keep in mind that neither of those and other audio files can be fed directly to machine learning models.