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The General Data Protection Regulation (GDPR), which came into effect on May 25, 2018, establishes strict guidelines for managing personal and sensitive data, backed by stiff penalties. GDPR’s requirements have forced some companies to shut down services and others to flee the EU market altogether. GDPR’s goal to give consumers control over their data and, thus, increase consumer trust in the digital ecosystem is laudable. However, there is a growing feeling that GDPR has dampened innovation in machine learning & AI applied to personal and/or sensitive data. After all, ML & AI are hungry for rich, detailed data and sanitizing data to improve privacy typically involves redacting or fuzzing inputs, which multiple studies have shown can seriously affect model quality and predictive power. While this is technically true for some privacy-safe modeling techniques, it’s not true in general. The root cause of the problem is two-fold. First, most data scientists have never learned how to produce great models with great privacy. Second, most companies lack the systems to make privacy-safe machine learning & AI easy. This talk will challenge the implicit assumption that more privacy means worse predictions. Using practical examples from production environments involving personal and sensitive data, the speakers will introduce a wide range of techniques–from simple hashing to advanced embeddings–for high-accuracy, privacy-safe model development. Key topics include pseudonymous ID generation, semantic scrubbing, structure-preserving data fuzzing, task-specific vs. task-independent sanitization and ensuring downstream privacy in multi-party collaborations. Special attention will be given to Spark-based production environments.
Talk by Jeffrey Yau. Video Rating: / 5
Taking a look at seasonal data (Sunspots) and creating a function that can be used to predict values in the future.
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Today we discuss the 5 top stocks under per share 2019 edition. I think all stock market investors and even stock market traders will enjoy this video today. Stocks under are pretty speculative, but sometimes you can find a diamond in the rough.Would you consider these stocks to watch or stocks to buy?
These 5 stocks i would buy if I was forced to buy only stocks less than lets say. Do you like any of these stocks under ? As a matter a fact a few of these stocks are stocks under . I would love to hear your opinion on these stocks for 2019 and going forward and if you know of better stocks that are under ? Enjoy!
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Financial Education Channel Video Rating: / 5
Follow my progress as I dive head first into investing, while trying not to lose it all!!
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Please note I am not a market professional. I am not responsible for any trading losses that may be experienced by following my wayward lead, in fact I recommend you don’t follow my lead. 🙂 Have fun and happy trading. Video Rating: / 5