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Quality Control Tips for Data Collection with Drone Surveying

Smart Data Collective

Here at Smart Data Collective, we never cease to be amazed about the advances in data analytics. We have been publishing content on data analytics since 2008, but surprising new discoveries in big data are still made every year. You will also want to know how to harvest the data that you get.

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Accountancy Today: A new reality: coronavirus’s impact on financial planning

Jet Global

The devastating news of increasing numbers of sufferers and fatalities is having an inevitable knock-on effect as authorities introduce stricter health measures around the world to reduce the spread of the virus. . Elsewhere, it was the worst weekly decline for stocks since the 2008 financial crisis. A new reality?

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Benchmarking Performance: Your Options, Dos, Don'ts and To-Die-Fors!

Occam's Razor

[See step four in the process for creating your Digital Marketing and Measurement Model.]. should be 1,356,000), you've set a clear line in the sand as to what performance will be declared a success or a failure at the end of the measurement time period. Just skip the we can give you data and benchmarks on performance bits.

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Our quest for robust time series forecasting at scale

The Unofficial Google Data Science Blog

First, the system may not be understood, and even if it was understood it may be extremely difficult to measure the relationships that are assumed to govern its behavior. They can arise from data collection errors or other unlikely-to-repeat causes such as an outage somewhere on the Internet. to 1.5%.

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FRTB: Will 2023 Finally be the Year?

Cloudera

The Fundamental Review of the Trading Book (FRTB), introduced by the Basel Committee on Banking Supervision (BCBS), will transform how banks measure risk. FRTB is designed to address some fundamental weaknesses that did not get addressed in the post-2008 financial crisis regulatory reforms.

Risk 55
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ML internals: Synthetic Minority Oversampling (SMOTE) Technique

Domino Data Lab

Further, imbalanced data exacerbates problems arising from the curse of dimensionality often found in such biological data. This renders measures like classification accuracy meaningless. The use of multiple measurements in taxonomic problems. The unreasonable effectiveness of data. Machine Learning, 57–78.