Remove category tennis
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The COCO dataset: All you need to know

Mlearning.ai

"annotations": [ { "id": int, "image_id": int, "category_id": int, "segmentation": RLE or [polygon], "area": float, "bbox": [x, y, width, height], "iscrowd": 0 or 1 } ] Categories: Provides a comprehensive list of label categories used within the dataset. "categories":

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Synthetic Data: A Model Training Solution

Viso.ai

A GAN works like a two-player tennis match, with two models competing against each other. These may include generating rare or extreme cases, adding noise or outliers, and balancing classes or categories. It outputs a probability score indicating the likelihood that a sample came from the real data set.

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Use no-code machine learning to derive insights from product reviews using Amazon SageMaker Canvas sentiment analysis and text analysis models

AWS Machine Learning Blog

Text analysis allows you to classify text into two or more categories using custom models. To train a text analysis custom model, you simply provide a dataset consisting of the text and the associated categories in a CSV file. The dataset requires a minimum of two categories and 125 rows of text per category.

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Flag harmful language in spoken conversations with Amazon Transcribe Toxicity Detection

AWS Machine Learning Blog

Today, we are excited to announce Amazon Transcribe Toxicity Detection , a machine learning (ML)-powered capability that uses both audio and text-based cues to identify and classify voice-based toxic content across seven categories, including sexual harassment, hate speech, threats, abuse, profanity, insults, and graphic language.

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Innovation for Inclusion: Hack.The.Bias with Amazon SageMaker

AWS Machine Learning Blog

Additionally, it highlights the specific parts of your input text related to each category of bias. He is also a huge tennis fan and enjoys playing board games a lot. As shown in the following screenshot, after you provide the text, the application generates a new version that is free from racial, ethnical, and gender biases.

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Amazon Comprehend document classifier adds layout support for higher accuracy

AWS Machine Learning Blog

Evaluate your document classification needs Identify the various types of documents they you may need to classify, along with the different classes or categories to support your use case. Label a sample of your documents with the appropriate categories or labels ( classes ). Document types may vary from PDF, Word, images, and so on.

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Extract non-PHI data from Amazon HealthLake, reduce complexity, and increase cost efficiency with Amazon Athena and Amazon SageMaker Canvas

AWS Machine Learning Blog

To overcome this, we use one-hot encoding, which converts each category in a column to a separate binary column, making the data suitable for a wider range of algorithms. In his spare time, Ramesh enjoys tennis, racquetball. Ramesh Dwarakanath is a Principal Solutions Architect at AWS based out of Boston, MA.

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