Guide
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Create a High-Quality Dataset for Reinforcement Learning from Human Feedback
RLHF has enabled language models trained on a general corpus of text data to be aligned with complex human values. This article details how you can train a reward model for RLHF on your own data.
Jimmy Whitaker
2023-05-11
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Human Feedback in AI: The Essential Ingredient for Success
In this article we explore the profound impact of human feedback on AI and examine how powerful tools like Label Studio are catalyzing a paradigm shift in AI training methodologies.
Jimmy Whitaker
2023-05-09
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To help you get started with data labeling, we've created this guide that outlines the best practices to ensure you label your data accurately.
Label Studio Team
2023-05-04
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Integrity, Accuracy, Consistency: 3 Keys to Maintaining Data Quality in Machine Learning
How do you identify and maintain high-quality data when you’re knee-deep in a project? And what does “data quality” mean in the context of machine learning? Read more to find out!
Nikolai Liubimov
2023-04-20
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Getting started with Object Detection
In this article, we’ll explore what object detection is, the challenges involved in implementing it, and share a step-by-step breakdown of getting started with this exciting technique.
Label Studio Team
2023-04-06
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What will the Long-Lasting Impacts of Large Generative Models Be?
Evaluating GPT-4’s release through the lens of open source data science leads us to see the possibility and potential for long-term impact — but it also reiterates the underlying importance of dataset development and context provided by human feedback through processes such as reinforcement learning through human feedback (RLHF) or human-in-the-loop processes.
Erin Mikail Staples
2023-03-21
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Contribute to the New Label Studio Community Docs
The Label Studio docs have a new look; with cleaner information architecture, and more ways to contribute.
Chris Hoge
2023-03-07
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Labeling Audio Data With Label Studio
In this guide, you'll learn how to set up an audio labeling project in Label Studio. Then we'll walk you through importing and labeling your data. You'll also see the many different features in Label Studio's audio labeling interface.
Erin Mikail Staples
2023-02-14
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Machine Learning Bias: What Is It, Why Is It Important, and What Can You Do About It?
A machine learning model can send unintended, dangerous conversational responses. Train your models to avoid these outcomes by learning what machine learning bias is and how to minimize it.
Label Studio Team
2022-11-30
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Implementing Audio Classification for Machine Learning Projects Using Label Studio
With this guide, learn how audio classification works and how to implement it when building audio ML projects, so you can optimize your ML models and build a better overall product.
Label Studio Team
2022-11-23
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Understanding Audio Classification: Everything You Need to Know
This article takes a look at audio classification and discusses the various use cases that can benefit from this technique.
Label Studio Team
2022-11-16
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How To Choose an Open-source Audio Classification Tool and 6 Options To Use
When choosing an annotation tool for your audio classification project, you need to carefully study its unique features and ensure that it works well with the rest of your stack. Finding the right tool will give you the best value in your audio classification projects.
Label Studio Team
2022-11-09
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Getting Started with Image Classification
In this guide, we dig into image classification—what it means, how it works, and the main steps to help you get started.
Label Studio Team
2022-11-02
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The Building Blocks of an Efficient Data Labeling Process
Instituting an efficient data labeling process is the key to eliminating inaccuracies in the data fed to machine learning models. Here are some generally applicable principles that can improve the efficiency and accuracy of your data labeling process.
Label Studio Team
2022-10-26
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Open Source Tools for Sentiment Analysis
Some developers and data scientists just want to grab code, download a repo and go. If that’s your style, choosing a fully-featured open source sentiment tool might be right choice for you.
Label Studio Team
2022-10-13
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6 Costly Data Labeling Mistakes and How To Avoid Them
Learn six of the most common data labeling mistakes we see in ML projects and the fixes that can help you maintain consistent, accurate training data.
Label Studio Team
2022-09-09
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Understanding Sentiment Analysis
This blog covers the basics of sentiment analysis: key components, use cases, challenges, and solutions.
Label Studio Team
2022-07-18
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Data Labeling: The Unsung Hero Combating Data Drift
Learn how various types of data drift and how data drift impacts model performance, along with several examples of how data labeling can tackle data drift.
Label Studio Team
2021-10-21
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10 important considerations for NLP labeling
The top 10 important considerations for NLP labeling and functionality in labeling tools for natural language processing machine learning projects.
Label Studio Team
2021-06-17