Data collection is the single most important step in solving any machine learning problem. As such, teams that dive head first into projects without considering the right data collection process often don't get the results they want. Fortunately, there are many data collection tools to help prepare training datasets quickly and at scale. The best data collection tools are easy to use, support a range of functionalities and file types, and preserve the overall integrity of data. In this article, we outline the best data collection tools for machine learning projects.
In modern text data analysis, NLP tools and NLP libraries are indispensable. Researchers and businesses use natural language processing tools to draw information from text data analysis. This analysis includes analyzing customer feedback, automating support systems, improving search and recommendation algorithms, and monitoring social media. There are a wide array of NLP tools and services available, and knowing their features is key to good results. While some tools are perfect for small projects, others are better for experts working on big data.
Whether you're a parent trying to make ends meet, a broke college student in need of extra cash or everything in between, working online jobs could help alleviate financial stress. For those of you looking for remote jobs to work from home, this article will introduce the top online jobs for moms, or anyone looking for an additional source of income. The following jobs include positions available at Lionbridge and Gengo and are subject to change. Are you multilingual with expert to native fluency in two or more languages? If so, you're in luck because online translation jobs are both plentiful and frequently available.
With the emergence of crowdsourcing platforms such as Amazon Mechanical Turk, more and more companies are making crowdsourced data a key component of their machine learning strategy. By engaging a group of crowdworkers, companies can distribute hundreds of thousands of machine learning microtasks quickly and cost-effectively. Listed below are just a few of the many advantages of using crowdsourced data in machine learning. A recent study by AI market research firm Cognilytica found that nearly 80% of time spent on AI projects revolves around collecting, cleaning, and labeling data. That leaves only 20% for model development, training and calibration.
Lionbridge, the world's most trusted globalization partner, is pleased to announce the launch of Lionbridge AI. Marrying the market-leading human-annotated AI training data services and linguistic capabilities of Lionbridge, formerly known as Machine Intelligence, with the data training platform and marketplace of recently-acquired Gengo, Lionbridge AI provides a suite of capabilities and services that meets the end-to-end needs of companies building the next generation of machine learning and artificial intelligence (AI) systems. "This is an incredible opportunity to bring together our services, technology platform and voice capabilities into a single offering," said Lionbridge CEO John Fennelly. "We are confident that Lionbridge AI will help our customers deliver improved, more engaging, and increasingly human-like experiences to their artificial intelligence initiatives." As nearly every company contemplates how to use AI to build smarter products and services, while determining how to derive greater predictive capabilities to strengthen the customer experience, Lionbridge AI is perfectly positioned to support the ever-expanding array of uses for artificial intelligence.