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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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30+ Free Datasets for Your Data Science Projects in 2023

Knowledge Hut

Whether you are working on a personal project, learning the concepts, or working with datasets for your company, the primary focus is a data acquisition and data understanding. In this article, we will look at 31 different places to find free datasets for data science projects. What is a Data Science Dataset?

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A Look At The Data Systems Behind The Gameplay For League Of Legends

Data Engineering Podcast

Summary The majority of blog posts and presentations about data engineering and analytics assume that the consumers of those efforts are internal business users accessing an environment controlled by the business. The biggest challenge with modern data systems is understanding what data you have, where it is located, and who is using it.

Systems 130
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Apache Ozone – A Multi-Protocol Aware Storage System

Cloudera

The vast tapestry of data types spanning structured, semi-structured, and unstructured data means data professionals need to be proficient with various data formats such as ORC, Parquet, Avro, CSV, and Apache Iceberg tables, to cover the ever growing spectrum of datasets – be they images, videos, sensor data, or other type of media content.

Systems 106
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D3: An Automated System to Detect Data Drifts

Uber Engineering

In this blog learn how we automated column-level drift detection in batch datasets at Uber scale, reducing the median time to detect issues in critical datasets by 5X. Data quality is of paramount importance at Uber, powering critical decisions and features.

Systems 84
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Netflix’s Distributed Counter Abstraction

Netflix Tech

By: Rajiv Shringi , Oleksii Tkachuk , Kartik Sathyanarayanan Introduction In our previous blog post, we introduced Netflix’s TimeSeries Abstraction , a distributed service designed to store and query large volumes of temporal event data with low millisecond latencies. Today, we’re excited to present the Distributed Counter Abstraction.

Datasets 100
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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.

Systems 77