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Top Open-Source Datasets to Train Machine Learning Models in 2021

Open-source datasets have massively contributed to the development of cutting-edge technology like machine learning and AI algorithms. These open-source datasets are known as data collections that are available for free access, modification, and sharing.  Machine learning models need sufficient datasets for training purposes to generate meaningful and in-depth insights efficiently and effectively. Thus, open-source datasets help to minimize potential barriers in data to train ML models.  Let’s explore some of the top open-source datasets to train machine learning models in 2021.

 

Top open-source datasets to train machine learning models

Google Dataset Search

Google Dataset Search is one of the top open-source datasets to train machine learning models with AI algorithms. It is home to around 25 million datasets for the use of data to train ML models efficiently and effectively. Programmers or developers can search with a simple keyword to seek open-source datasets in thousands of repositories in the Internet world. It helps to foster a data-sharing ecosystem for data to train ML models with AI algorithms and machine learning. It has promised ample growth in the variety and coverage of datasets for machine learning models.

 

AWS

AWS or Amazon Web Services is focused to be one of the popular open-source datasets to provide sufficient data to train ML models. This platform is useful for machine learning models for providing multiple open-source datasets in multiple fields like public transport, satellite images, and many more. Developers also get access to a search box to seek the right datasets with the minute details such as dataset description as well as its usage. These millions of datasets are already stored in AWS resources including Amazon S3. This cloud service is useful for getting access to data to train ML models and transfer the datasets as soon as possible.

 

Kaggle

Kaggle is one of the top open-source datasets to train ML models with more than 50,000 public datasets and 40,000 public notebooks. It helps to explore and analyze high-quality data in one of the largest open-source dataset libraries on the Internet. It is known as the community-driven machine learning platform with multiple tutorials as well as uploading options for developers.  It consists of a diverse set of compelling and independently contributed datasets for machine learning models.

 

Azure Open Datasets

Microsoft Azure Open Datasets are becoming a popular open-source dataset to enhance the accuracy level of machine learning models with AI algorithms and machine learning. There are publicly available datasets to save time and focus on training ML models efficiently and effectively. Azure incorporates features from curated datasets into multiple machine learning models to reduce the extra time for data preparation. Developers and data scientists can deliver insights at hyper-scale by leveraging Microsoft Azure Open Datasets and its data analytics solutions.

 

Appen Datasets Resource Center

Appen Datasets Resource Center provides high-quality licensable datasets that are sufficient data to train ML models. There is an extensive catalog of ‘Off-the-Shelf’ open-source datasets that consist of more than 11,000 hours of audio as well as over 25,000 images with 8.7 million words in 80 languages. This open-source dataset offers to enhance accuracy in machine learning models with high performance in AI algorithms. It is focused on meeting the needs of the global customer base who wants data to train ML models.

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