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Taktile makes it easier to leverage machine learning in the financial industry

TechCrunch

Meet Taktile , a new startup that is working on a machine learning platform for financial services companies. This isn’t the first company that wants to leverage machine learning for financial products. They could use that data to train new models and roll out machine learning applications.

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CatalyzeX grabs $1.64M seed to help developers find right machine learning model

TechCrunch

Machine learning is exploding, and so are the number of models out there for developers to choose from. The company co-founders, brothers Gaurav Ragtah and Himanshu Ragtah, saw that there was so much research being done and wanted to build a tool to make it easier for developers to find the most applicable models for their use case.

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Hugging Face reaches $2 billion valuation to build the GitHub of machine learning

TechCrunch

Lux Capital is leading the round, with Sequoia and Coatue investing in the company for the first time. When I first covered the company in 2017, the startup was focused on a consumer app. That consumer bet hasn’t paid off, but the company kept iterating on its natural language processing technology.

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Leveraging AMPs for machine learning

CIO

Even less experienced technical professionals can now access pre-built technologies that accelerate the time from ideation to production. As a result, many companies are now more exposed to security vulnerabilities, legal risks, and potential downstream costs. For more on Cloudera’s AMPs, click here.

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5 Things a Data Scientist Can Do to Stay Current

And more is being asked of data scientists as companies look to implement artificial intelligence (AI) and machine learning technologies into key operations. Fostering collaboration between DevOps and machine learning operations (MLOps) teams. Collecting and accessing data from outside sources.

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Build a strong data foundation for AI-driven business growth

CIO

In the quest to reach the full potential of artificial intelligence (AI) and machine learning (ML), there’s no substitute for readily accessible, high-quality data. Achieving ROI from AI requires both high-performance data management technology and a focused business strategy.

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The key to operational AI: Modern data architecture

CIO

For companies investing in data science, realizing the return on these investments requires embedding AI deeply into business processes. Adopting Operational AI Organizations looking to adopt Operational AI must consider three core implementation pillars: people, process, and technology.

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Data Science Fails: Building AI You Can Trust

The game-changing potential of artificial intelligence (AI) and machine learning is well-documented. Any organization that is considering adopting AI at their organization must first be willing to trust in AI technology.

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Realizing the Benefits of Automated Machine Learning

While everyone is talking about machine learning and artificial intelligence (AI), how are organizations actually using this technology to derive business value? This white paper covers: What’s new in machine learning and AI. Real-world examples of companies using the DataRobot automated machine learning platform.