Co-authors: Sriram Vasudevan, Cyrus DiCiccio, and Kinjal Basu At LinkedIn, our imperative is to create economic opportunity for every member of the global workforce, something that would be impossible to accomplish without leveraging AI at scale. We help members and customers make decisions by providing them with the most relevant insights based on the available...
Open Source Articles
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- Topics:
- Spark,
- artificial intelligence,
- machine learning,
- Data,
- Open Source
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Co-authors: Weiwei Guo, Xiaowei Liu, Sida Wang, Huiji Gao, and Bo Long Natural language processing (NLP) technologies are widely deployed to process rich natural language text data for search and recommender systems. Achieving high-quality search and recommendation results requires that information, such as user queries and documents, be processed and understood...
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Co-authors: Cong Gu, Abin Shahab, Chen Qiang, and Keqiu Hu Editor's note: This blog has been updated. LinkedIn AI has been traditionally Hadoop/YARN based, and we operate one of the world’s largest Hadoop data lakes, with over 4,500 users and 500PB of data. In the last few years, Kubernetes has also become very popular at LinkedIn for Artificial Intelligence (AI...
- Topics:
- Hadoop,
- Security,
- Open Source
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Co-authors: Jun Shi, Mingzhou Zhou Introduction In the machine learning community, Apache Spark is widely used for data processing due...
- Topics:
- Spark,
- machine learning,
- TensorFlow,
- Data,
- Open Source
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Built at LinkedIn, Pinot is an open source, distributed, and scalable OLAP data store that we use as our de-facto near-real-time...
- Topics:
- Pinot,
- metrics,
- Data,
- Open Source
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Co-authors: Kerem Sahin, Mars Lan, and Shirshanka Das Finding the right data quickly is critical for any company that relies on big...
- Topics:
- Metadata,
- infrastructure,
- Data,
- Open Source