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Machine Learning Data Strategy
Want to improve your machine learning training data? We created this white paper for business executives embarking on-or looking to improve-their own machine learning projects. In this white paper, we share:
- The Importance of Quantity and why machines need a large volume of data to learn. Think of machine learning data like survey data: the larger and more complete your sample size and dataset, the more reliable your conclusions will be.
- Why Quality Matters and why the right training data is essential for success. You can have the most appropriate algorithm, but if you train your machine on bad data, then it will learn the wrong lessons.
- The Different Types of Source Data: Learn about the four main sources of data and determine where your data should come from.
Trusted by 8 of the world’s top 10 tech companies to deliver high-quality data for machine learning. Appen is a global leader in the development of high-quality, human-annotated datasets for machine learning and artificial intelligence. With deep expertise in more than 180 languages and access to a global crowd of over 1 million skilled contractors, Appen partners with technology, automotive and eCommerce companies – as well as governments worldwide – to help them develop, enhance and use products that rely on natural languages and machine learning.
An Introduction to Machine Learning Training Data
Maximize your machine learning program and understand why training data quality is crucial to the success of your machine learning program.