Remove 2006 Remove Modeling Remove Risk Remove Uncertainty
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The trinity of errors in financial models: An introductory analysis using TensorFlow Probability

O'Reilly on Data

An exploration of three types of errors inherent in all financial models. At Hedged Capital , an AI-first financial trading and advisory firm, we use probabilistic models to trade the financial markets. All financial models are wrong. Clearly, a map will not be able to capture the richness of the terrain it models.

Modeling 134
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Accelerating VMware’s growth

CIO Business Intelligence

Unlocking VMware’s potential Broadcom’s business model and its decades of focus on R&D combined with VMware’s core technology and superb talent will be the catalysts that will enable VMware to capture the growth opportunity in front of it. He has held this position since March 2006. To learn more, visit Broadcom.

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Coding for the Future of U.S. National Defense

CIO Business Intelligence

VMware Tanzu Labs partners with organizations worldwide to accelerate the delivery of software and modernize legacy apps, while reducing operating costs and risk working side by side with customers to build capabilities, transfer skills and knowledge, and instill a process that shows immediate and lasting impact. government.

Software 102
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Broadcom’s Approach Towards Delivering Customer Value

CIO Business Intelligence

Instead, our entire business model is grounded in the belief that we can create innovative solutions that will deliver on our customers’ needs over time and progress through multiple generations of technology. He has held this position since March 2006. We co-create with them, and we invest in continuously addressing their needs.

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What a Combined Broadcom and VMware Can Deliver to Our Customers

CIO Business Intelligence

The Broadcom business case for this transaction is premised on focusing on the business model, increasing R&D, and executing so that customers see the value of the full portfolio of innovative product offerings — not on increasing prices. He has held this position since March 2006.

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Our quest for robust time series forecasting at scale

The Unofficial Google Data Science Blog

Selection and aggregation of forecasts from an ensemble of models to produce a final forecast. Quantification of forecast uncertainty via simulation-based prediction intervals. Calendaring was therefore an explicit feature of models within our framework, and we made considerable investment in maintaining detailed regional calendars.

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Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

Crucially, it takes into account the uncertainty inherent in our experiments. Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well. It is a big picture approach, worthy of your consideration.