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Streaming data to a BigQuery table with GCP

Mlearning.ai

BigQuery is very useful in terms of having a centralized location of structured data; ingestion on GCP is wonderful using the ‘bq load’ command line tool for uploading local .csv PubSub and Dataflow are solutions for storing newly created data from website/application activity, in either BigQuery or Google Cloud Storage.

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Training Models on Streaming Data [Practical Guide]

The MLOps Blog

These days when you are listening to a song or a video, if you have auto-play on, the platform creates a playlist for you based on your real-time streaming data. It provides a web-based interface for building data pipelines and can be used to process both batch and streaming data. pip install tensorflow== 2.7.1 !pip

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Boost employee productivity with automated meeting summaries using Amazon Transcribe, Amazon SageMaker, and LLMs from Hugging Face

AWS Machine Learning Blog

The service allows for simple audio data ingestion, easy-to-read transcript creation, and accuracy improvement through custom vocabularies. They are designed for real-time, interactive, and low-latency workloads and provide auto scaling to manage load fluctuations. AWS CDK version 2.0

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Orchestrate Ray-based machine learning workflows using Amazon SageMaker

AWS Machine Learning Blog

With Ray and AIR, the same Python code can scale seamlessly from a laptop to a large cluster. Ingesting features into the feature store contains the following steps: Define a feature group and create the feature group in the feature store. Ingest the prepared data into the feature group by using the Boto3 SDK.

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MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

For example, if your team is proficient in Python and R, you may want an MLOps tool that supports open data formats like Parquet, JSON, CSV, etc., This includes features for data labeling, data versioning, data augmentation, and integration with popular data storage systems. Can you render audio/video?

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How to Build ML Model Training Pipeline

The MLOps Blog

Complete ML model training pipeline workflow | Source But before we delve into the step-by-step model training pipeline, it’s essential to understand the basics, architecture, motivations, challenges associated with ML pipelines, and a few tools that you will need to work with. We will use Python and the popular Scikit-learn.

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