Dive deep into machine learning for only $35.

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Machine learning applications today begin life as models. These must be updated and maintained once they're in the field if enterprises want to truly succeed with the technology. This wide-ranging Talking Data podcast looks at the journey from the lab.

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Machine learning provides a potential to far better manage enterprise information in today’s distributed world. While the industry looks at ways to ask better questions, it needs to be looking at how to locate and manage the information that provides answers.

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So many advertising and creative decisions are based on guesses and preconceived ideas. AI can discover new approaches humans would miss.

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In this SearchCIO Q&A, Aanchal Gupta, directory of security at Facebook, explains how the social media company is implementing machine learning to flag inappropriate content and accounts and to detect unrecognized logins.

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: THE BUSINESS TIMES Opinion - RECENT technology advancements have placed Artificial Intelligence (AI), along with its subfield of Machine Learning (ML), at the forefront of transforming the accounting industry. Major accounting practices are starting to implement ML to streamline their operations with the aim of achieving time and cost reduction, increased productivity and improved accuracy. . Read more at The Business Times.

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An early review of Udacity's AI, Python, and machine learning Nanodegree programs

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Agencies at every level -- local, state and federal -- are increasingly using AI and machine learning to better understand data and make back-office tasks more efficient.

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By discovering patterns hidden in existing operational data, companies can significantly improve the performance, throughput, quality, and yield of industrial operations.

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This article is based on Rachel Thomas’s keynote presentation, “Analyzing & Preventing Unconscious Bias in Machine Learning” at QCon.ai 2018. Rachel talks about the pitfalls and risk the bias in machine learning brings to the decision-making process. She discusses three use cases of machine learning bias.

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