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How to get datasets for Machine Learning?

Knowledge Hut

Datasets are the repository of information that is required to solve a particular type of problem. Datasets play a crucial role and are at the heart of all Machine Learning models. Datasets are often related to a particular type of problem and machine learning models can be built to solve those problems by learning from the data.

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Building for Inclusivity: The Technical Blueprint of Pinterest’s Multidimensional Diversification

Pinterest Engineering

Our commitment is evidenced by our history of building products that champion inclusivity. We know from experience that building for marginalized communities helps make the product work better for everyone. In this case, thousands of fashion Pins¹ publicly available on Pinterest are gathered to serve as the raw dataset.

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Building a Winning Data Quality Strategy: Step by Step

Databand.ai

Building a Winning Data Quality Strategy: Step by Step Eitan Chazbani August 30, 2023 What Is a Data Quality Strategy? This includes defining roles and responsibilities related to managing datasets and setting guidelines for metadata management. Data profiling: Regularly analyze dataset content to identify inconsistencies or errors.

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Best of 2022: Top 5 Financial Services Blog Posts

Precisely

Let’s further explore the impact of data in this industry as we count down the top 5 financial services blog posts of 2022. #5 By using industry-leading dataset and analytical techniques, you can overcome historical limitations through an approach called “opportunity-based goal setting.”

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Building a Data-Centric Platform for Generative AI and LLMs at Snowflake

Snowflake

Snowflake users are already taking advantage of LLMs to build really cool apps with integrations to web-hosted LLM APIs using external functions , and using Streamlit as an interactive front end for LLM-powered apps such as AI plagiarism detection , AI assistant , and MathGPT. Join us in Vegas at our Summit to learn more.

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Data News — Week 24.16

Christophe Blefari

It was trained on a large dataset containing 15T tokens (compared to 2T for Llama 2). This blog shows how you can use Gen AI to evaluate inputs like translations with added reasons. How we build Slack AI to be secure and private — How Slack uses VPC and Amazon SageMaker with your data secured and private.

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Building a large scale unsupervised model anomaly detection system?—?Part 2

Lyft Engineering

Building a large scale unsupervised model anomaly detection system — Part 2 Building ML Models with Observability at Scale By Rajeev Prabhakar , Han Wang , Anindya Saha Photo by Octavian Rosca on Unsplash In our previous blog we discussed the different challenges we faced for model monitoring and our strategy for addressing some of these problems.

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