Occam's Razor

MAY 14, 2012

It used to fall behind lag the other two in brand queries, but you can see how starting late 2009 (bad year for Target in this context) Amazon overtook Target and now (2011, 2012) is casting a big shadow over Target. They are full of specific insights you can use to optimize your online search campaigns. Five Caveats!

Measurement 128

Measurement Analytics Advertising Marketing 128

The Unofficial Google Data Science Blog

APRIL 17, 2017

For us, demand for forecasts emerged from a determination to better understand business growth and health, more efficiently conduct day-to-day operations, and optimize longer-term resource planning and allocation decisions. Prediction Intervals A statistical forecasting system should not lack uncertainty quantification. 1990): 3. [3]

Forecasting 83

Forecasting Modeling Statistics Uncertainty 83

AWS Big Data

MARCH 21, 2024

The data becomes available in Amazon Redshift within seconds, allowing you to use the analytics features of Amazon Redshift and capabilities like data sharing, workload optimization autonomics, concurrency scaling, machine learning, and many more. For DB instance identifier , enter zero-etl-source-rms. Choose Create policy.

Data Warehouse 84

Data Warehouse Metrics Optimization Statistics 84

Domino Data Lab

APRIL 21, 2021

In contrast, the decision tree classifies observations based on attribute splits learned from the statistical properties of the training data. Machine Learning-based detection – using statistical learning is another approach that is gaining popularity, mostly because it is less laborious. 3f" % x) dataDF.describe().

Statistics 69

Statistics Machine Learning Modeling Metrics 69

The Unofficial Google Data Science Blog

AUGUST 27, 2019

This problem can be phrased as an optimization problem — given some fixed review capacity how should we sample videos? But importance sampling in statistics is a variance reduction technique to improve the inference of the rate of rare events, and it seems natural to apply it to our prevalence estimation problem.

Metrics 98

Metrics Statistics Uncertainty Optimization 98

Domino Data Lab

JULY 22, 2019

He was saying this doesn’t belong just in statistics. It involved a lot of work with applied math, some depth in statistics and visualization, and also a lot of communication skills. I went to a meeting at Starbucks with the founder of Alation right before they launched in 2012, drawing on the proverbial back-of-the-napkin.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

The Unofficial Google Data Science Blog

JULY 11, 2017

SCOTT Time series data are everywhere, but time series modeling is a fairly specialized area within statistics and data science. They may contain parameters in the statistical sense, but often they simply contain strategically placed 0's and 1's indicating which bits of $alpha_t$ are relevant for a particular computation. by STEVEN L.

Forecasting 64

Forecasting Statistics Modeling Software 64

Occam's Razor

SEPTEMBER 21, 2015

The Directors, the Marketers, the Optimization employees and our resident social media gurus. You can cut yourself with it and embarrass yourself, or you can look the very best you ever have by using it optimally. Second, between 2012 and 2013. We still live in an world where we are optimize for single visit sessions.

Visualization 160

Visualization Key Performance Indicator Slice and Dice Strategy 160

Sisense

DECEMBER 11, 2019

An exciting slate of presentations took them on a journey from why to how they should use data analytics to optimize their operations successfully and maximize their business opportunities. From a startup in 2012, it is now valued at $3.2 Optimizing data pipelines: How Kongregate uses Periscope Data. A true unicorn.

Data Lake 80

Data Lake Big Data Sales Data-driven 80

The Unofficial Google Data Science Blog

MARCH 31, 2016

We often use statistical models to summarize the variation in our data, and random effects models are well suited for this — they are a form of ANOVA after all. Cambridge University Press, (2012). [4] Journal of the American Statistical Association 68.341 (1973): 117-130. [5] Journal of the American Statistical Association, Vol.

Modeling 40

Modeling Statistics Advertising Testing 40

Occam's Razor

JANUARY 10, 2011

10% of your time should be spent in implementing tools, not 15 months with an eye towards analysis in the middle of 2012. And possess at least some knowledge of the fundamentals of statistics. But how can you optimize it for the fact that the person voted in the election?" Stop switching tools! And using Site Catalyst.

Analytics 120

Analytics Measurement Data-driven Optimization 120

Domino Data Lab

MARCH 3, 2019

While image data has been the stalwart for deep learning use cases since the proverbial “ AlexNet moment ” in 2011-2012, and a renaissance in NLP over the past 2-3 years has accelerated emphasis on text use cases, we note that structured data is at the top of the list in enterprise. Spark, Kafka, TensorFlow, Snowflake, etc.,

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

CIO Business Intelligence

FEBRUARY 3, 2023

The company also has systems optimized for industries such as supply chain management ( TradeEdge ) or banking. Power Advisor tracks statistics about performance to locate bottlenecks and other issues. Rocketbot Orquestador will manage them, running them as needed while compiling statistics.

Data-driven 145

Data-driven Interactive Enterprise Statistics 145

Domino Data Lab

SEPTEMBER 25, 2019

A big part of statistics, particularly for financial and econometric data, is analyzing time series, data that are autocorrelated over time. Fortunately, the forecast package has a number of functions to make working with time series data easier, including determining the optimal number of diffs. The result is shown in Figure 24.4. >

Forecasting 87

Forecasting Modeling Statistics Optimization 87

O'Reilly on Data

MAY 21, 2019

Consider deep learning, a specific form of machine learning that resurfaced in 2011/2012 due to record-setting models in speech and computer vision. Another algorithm (the “trainer” and “pipeline”) that uses data to produce the Model that best optimizes some objective function. Use ML to unlock new data types—e.g.,

Machine Learning 238

Machine Learning Technology Deep Learning Data Science 238

The Unofficial Google Data Science Blog

OCTOBER 12, 2017

1]" Statistics, as a discipline, was largely developed in a small data world. More people than ever are using statistical analysis packages and dashboards, explicitly or more often implicitly, to develop and test hypotheses. This question is statistical or methodological in nature. Know what matters.

Experimentation 61

Experimentation Testing Statistics Metrics 61