Google is acquiring Kaggle, which hosts competitions for data scientists. That report comes from TechCrunch, which was the first tech publication to report that Google was exploring such an acquisition. Terms of the deal went undisclosed. Google confirmed the buy at its Google Cloud Next conference in San Francisco, and the move certainly makes sense: as a company that lives on data, Google has a pressing and continuous need for the data scientists who power Kaggle’s community and competitions. Kaggle currently offers three services: data-science competitions (projects include using datasets to better detect lung cancer), public datasets (useful for data analytics), and kernels (people can get feedback on their code). For years, companies such as Microsoft and NASA have used Kaggle to crowdsource enormous data challenges, including gesture recognition, dark-matter imaging, and even airline arrival times. Kaggle also boasts a high degree of loyalty among data scientists. “There are some pretty amazing people who compete,” Kaggle co-founder and CEO Anthony Goldbloom told Dice in 2013. “And some enter 80 or more times per contest, devoting a lot of their time.” By purchasing Kaggle, Google gains access to a pipeline of data scientists and projects. Considering the intense competition among tech firms for professionals skilled in data analytics, that could give the company a decided advantage when it comes to crafting new products and services. For those tech pros interested in seeing what Google’s been doing in terms of data tools, check out TensorFlow, the company’s deep-learning architecture (along with an open-source software library). A three-hour course on the Google Cloud Platform blog also gives an intro to deep-learning fundamentals. The Google Cloud Platform offers a variety of artificial intelligence APIs, such as one that analyzes unstructured text. As more and more companies fold A.I. and machine learning into their business plans, working knowledge of these tools will only become increasingly important. Google Acquires Kaggle, Data-Scientist Hub
Google is acquiring Kaggle, which hosts competitions for data scientists. That report comes from TechCrunch, which was the first tech publication to report that Google was exploring such an acquisition. Terms of the deal went undisclosed. Google confirmed the buy at its Google Cloud Next conference in San Francisco, and the move certainly makes sense: as a company that lives on data, Google has a pressing and continuous need for the data scientists who power Kaggle’s community and competitions. Kaggle currently offers three services: data-science competitions (projects include using datasets to better detect lung cancer), public datasets (useful for data analytics), and kernels (people can get feedback on their code). For years, companies such as Microsoft and NASA have used Kaggle to crowdsource enormous data challenges, including gesture recognition, dark-matter imaging, and even airline arrival times. Kaggle also boasts a high degree of loyalty among data scientists. “There are some pretty amazing people who compete,” Kaggle co-founder and CEO Anthony Goldbloom told Dice in 2013. “And some enter 80 or more times per contest, devoting a lot of their time.” By purchasing Kaggle, Google gains access to a pipeline of data scientists and projects. Considering the intense competition among tech firms for professionals skilled in data analytics, that could give the company a decided advantage when it comes to crafting new products and services. For those tech pros interested in seeing what Google’s been doing in terms of data tools, check out TensorFlow, the company’s deep-learning architecture (along with an open-source software library). A three-hour course on the Google Cloud Platform blog also gives an intro to deep-learning fundamentals. The Google Cloud Platform offers a variety of artificial intelligence APIs, such as one that analyzes unstructured text. As more and more companies fold A.I. and machine learning into their business plans, working knowledge of these tools will only become increasingly important. 
