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TechCrunch+ roundup: New VC rules, AI biotech investor survey, Instagram ad case study

TechCrunch

Biotech firms widely use AI and machine learning to reduce R&D spending and bring products to market faster, but “the bigger question for investors is getting a better understanding of what exactly AI is attempting to model and predict,” says Shaq Vayda, principal at Lux Capital.

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Article: Testing Machine Learning: Insight and Experience from Using Simulators to Test Trained Functionality

InfoQ Culture Methods

When testing machine learning systems, we must apply existing test processes and methods differently. Machine Learning applications consist of a few lines of code, with complex networks of weighted data points that form the implementation.

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How companies around the world apply machine learning

O'Reilly Media - Data

Strata Data London will introduce technologies and techniques; showcase use cases; and highlight the importance of ethics, privacy, and security. The growing role of data and machine learning cuts across domains and industries. Data Science and Machine Learning sessions will cover tools, techniques, and case studies.

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How to take machine learning from exploration to implementation

O'Reilly Media - Data

Interest in machine learning (ML) has been growing steadily , and many companies and organizations are aware of the potential impact these tools and technologies can have on their underlying operations and processes. Machine Learning in the enterprise". Scalable Machine Learning for Data Cleaning.

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How Banks Are Winning with AI and Automated Machine Learning

By leveraging the power of automated machine learning, banks have the potential to make data-driven decisions for products, services, and operations. Read the white paper, How Banks Are Winning with AI and Automated Machine Learning, to find out more about how banks are tackling their biggest data science challenges.

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Audio Analysis With Machine Learning: Building AI-Fueled Sound Detection App

Altexsoft

Today, we have AI and machine learning to extract insights, inaudible to human beings, from speech, voices, snoring, music, industrial and traffic noise, and other types of acoustic signals. At the same time, keep in mind that neither of those and other audio files can be fed directly to machine learning models.

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Article: How I Contributed as a Tester to a Machine Learning System: Opportunities, Challenges and Learnings

InfoQ Culture Methods

Have you ever wondered about systems based on machine learning? In those cases, testing takes a backseat. And even if testing is done, it’s done mostly by developers itself. A tester’s role is not clearly portrayed. Testers usually struggle to understand ML-based systems and explore what contributions they can make.

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How Banks Are Winning with AI and Automated Machine Learning

By leveraging the power of automated machine learning, banks have the potential to make data-driven decisions for products, services, and operations. Read the whitepaper, How Banks Are Winning with AI and Automated Machine Learning, to find out more about how banks are tackling their biggest data science challenges.