Smart Data Collective

APRIL 5, 2022

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. Do an Overcast Survey to Ensure You Get Reliable Data.

Data Collection 108

Data Collection Data Quality Big Data Data-driven 108

The Unofficial Google Data Science Blog

APRIL 17, 2017

Selection and aggregation of forecasts from an ensemble of models to produce a final forecast. We conclude with an example of our forecasting routine applied to publicly available Turkish Electricity data. Finally, the time series model may give more accurate forecasts than an explanatory or mixed model.

Forecasting 83

Forecasting Modeling Statistics Uncertainty 83

Occam's Razor

OCTOBER 14, 2014

See step four in the process for creating your Digital Marketing and Measurement Model.]. But it is often a million times simpler to create your first set of benchmarks using your own data/performance. If you've read my first book Web Analytics: An Hour A Day, you know that I've advocated this strategy since 2008!

Key Performance Indicator 135

Key Performance Indicator Metrics Reporting Marketing 135

AWS Big Data

FEBRUARY 1, 2024

Large language models (LLMs) are becoming increasing popular, with new use cases constantly being explored. This is where model fine-tuning can help. Before you can fine-tune a model, you need to find a task-specific dataset. Next, we use Amazon SageMaker JumpStart to fine-tune the Llama 2 model with the preprocessed dataset.

Metadata 109

Metadata Modeling Data Processing Unstructured Data 109

Domino Data Lab

JULY 22, 2019

data science’s emergence as an interdisciplinary field – from industry, not academia. why data governance, in the context of machine learning is no longer a “dry topic” and how the WSJ’s “global reckoning on data governance” is potentially connected to “premiums on leveraging data science teams for novel business cases”.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Smart Data Collective

FEBRUARY 28, 2023

Here at Smart Data Collective, we have blogged extensively about the changes brought on by AI technology. Risk Parity was one of Andrew Zaytsev of Alan Biller and Partners’ investing categories in 2008. However, finetuning these models is a big part of the process.

Machine Learning 86

Machine Learning Risk Cost-Benefit Marketing 86

Cloudera

MARCH 18, 2021

FRTB is designed to address some fundamental weaknesses that did not get addressed in the post-2008 financial crisis regulatory reforms. A revised internal models approach (IMA) combined with an overhaul of the standardized approach (SA). Expanded requirements for a centralized and secure single view of risk data. .

Machine Learning 56

Machine Learning Risk Risk Management Measurement 56