The Unofficial Google Data Science Blog

APRIL 23, 2024

If $Y$ at that point is (statistically and practically) significantly better than our current operating point, and that point is deemed acceptable, we update the system parameters to this better value. And we can keep repeating this approach, relying on intuition and luck. Why experiment with several parameters concurrently?

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

CIO Business Intelligence

MAY 12, 2022

The tools include sophisticated pipelines for gathering data from across the enterprise, add layers of statistical analysis and machine learning to make projections about the future, and distill these insights into useful summaries so that business users can act on them. A free plan allows experimentation. On premises or in SAP cloud.

Predictive Analytics 137

Predictive Analytics Analytics Statistics Machine Learning 137

CIO Business Intelligence

APRIL 12, 2024

Right now most organizations tend to be in the experimental phases of using the technology to supplement employee tasks, but that is likely to change, and quickly, experts say.

Experimentation 143

Experimentation Reporting Testing Statistics 143

Occam's Razor

NOVEMBER 17, 2008

There is a tendency to think experimentation and testing is optional. So you don't have to worry about integrations with analytics tools, you don't have to worry about rushing to get a PhD in Statistics to interpret results and what not. So as my tiny gift for you here are five experimentation and testing ideas for you.

Testing 113

Testing Experimentation Risk Optimization 113

O'Reilly on Data

DECEMBER 9, 2019

We develop an ordinary least squares (OLS) linear regression model of equity returns using Statsmodels, a Python statistical package, to illustrate these three error types. CI theory was developed around 1937 by Jerzy Neyman, a mathematician and one of the principal architects of modern statistics. and an error term ??

Statistics 32

Statistics Uncertainty Risk Marketing 32

Business Over Broadway

AUGUST 4, 2020

Experimentation and iteration to improve existing ML models (39%). In prior research, I found that data professionals who self-identified as Researchers have a strong math/statistics/research skill set. The entire list of activities (shown in Figure 1) were: Analyze and understand data to influence product or business decisions (63%).

Machine Learning 145

Machine Learning Data Science Statistics Experimentation 145

The Unofficial Google Data Science Blog

JULY 22, 2020

For example, imagine a fantasy football site is considering displaying advanced player statistics. A ramp-up strategy may mitigate the risk of upsetting the site’s loyal users who perhaps have strong preferences for the current statistics that are shown. One reason to do ramp-up is to mitigate the risk of never before seen arms.

Experimentation 96

Experimentation Statistics Testing Knowledge Discovery 96

O'Reilly on Data

MARCH 18, 2020

It seems as if the experimental AI projects of 2019 have borne fruit. data cleansing services that profile data and generate statistics, perform deduplication and fuzzy matching, etc.—or This year, about 15% of respondent organizations are not doing anything with AI, down ~20% from our 2019 survey. But what kind?

Enterprise 349

Enterprise Deep Learning Data Governance Risk 349

The Unofficial Google Data Science Blog

DECEMBER 14, 2021

Some of that uncertainty is the result of statistical inference, i.e., using a finite sample of observations for estimation. But there are other kinds of uncertainty, at least as important, that are not statistical in nature. Among these, only statistical uncertainty has formal recognition.

Uncertainty 56

Uncertainty Statistics Measurement Cost-Benefit 56

CIO Business Intelligence

JANUARY 19, 2024

The US Bureau of Labor Statistics (BLS) forecasts employment of data scientists will grow 35% from 2022 to 2032, with about 17,000 openings projected on average each year. You should also have experience with pattern detection, experimentation in business optimization techniques, and time-series forecasting.

Data Science 126

Data Science Machine Learning Predictive Modeling Forecasting 126

Rocket-Powered Data Science

JULY 7, 2019

Computer Vision: Data Mining: Data Science: Application of scientific method to discovery from data (including Statistics, Machine Learning, data visualization, exploratory data analysis, experimentation, and more). They cannot process language inputs generally. Examples: (1) Automated manufacturing assembly line. (2) 4) Prosthetics.

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

Data Science 101

JANUARY 15, 2020

Some pitfalls of this type of experimentation include: Suppose an experiment is performed to observe the relationship between the snack habit of a person while watching TV. Bias can cause a huge error in experimentation results so we need to avoid them. Statistics Essential for Dummies by D. REFERENCES. McCabe & B.

Experimentation 96

Experimentation Statistics Measurement Testing 96

CIO Business Intelligence

JUNE 14, 2023

Candidates are required to complete a minimum of 12 credits, including four required courses: Algorithms for Data Science, Probability and Statistics for Data Science, Machine Learning for Data Science, and Exploratory Data Analysis and Visualization.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

CIO Business Intelligence

JULY 31, 2024

For teams that want to boil down their own data into predictive tools, Model Builder will turn all those records of past purchases sitting in the data lake into a big statistical hair ball of tendencies that passes for an AI these days. Salesforce is pushing the idea that Einstein 1 is a vehicle for experimentation and iteration.

Data Lake 119

Data Lake IT Sales Experimentation 119

O'Reilly on Data

APRIL 19, 2021

We’ll look at this later, but being able to reproduce experimental results is critical to any science, and it’s a well-known problem in AI. It’s more concerning that workflow reproducibility (3%) is in second-to-last place. This makes sense, given that we don’t see heavy usage of tools for model and data versioning. Maturity by Continent.

Enterprise 364

Enterprise Risk Modeling Manufacturing 364

Occam's Razor

AUGUST 22, 2011

Build A Great Web Experimentation & Testing Program. Experimentation and Testing: A Primer. Tip #9: Leverage Statistical Control Limits. Tip#1: Statistical Significance. Web Analytics Career Advice: Statistics, Business, IT & Mushrooms. Eight Tips For Choosing An Online Survey Provider. Got Surveys?

KPI 125

KPI Metrics Measurement ROI 125

FineReport

DECEMBER 11, 2019

. – Head First Data Analysis: A learner’s guide to big numbers, statistics, and good decisions. The big news is that we no longer need to be proficient in math or statistics, or even rely on expensive modeling software to analyze customers. By Michael Milton. – Data Divination: Big Data Strategies.

Big Data 98

Big Data Statistics Experimentation Data Strategy 98

CIO Business Intelligence

SEPTEMBER 30, 2024

Once we get more data from across a couple of areas into Mquiry, I would love to see the insights it might show us and do some training against that data.

Data Quality 116

Data Quality Experimentation Insurance Statistics 116

CIO Business Intelligence

MARCH 21, 2022

According to William Chen, Data Science Manager at Quora , the top five skills for data scientists include a mix of hard and soft skills: Programming: The “most fundamental of a data scientist’s skill set,” programming improves your statistics skills, helps you “analyze large datasets,” and gives you the ability to create your own tools, Chen says.

Unstructured Data 137

Unstructured Data Data Analytics Analytics Data Science 137

CIO Business Intelligence

JANUARY 2, 2024

He plans to scale his company’s experimental generative AI initiatives “and evolve into an AI-native enterprise” in 2024. But at the end of the day, it boils down to statistics. Statistics can be very misleading. That’s the case for Yi Zhou, CTO and CIO with Adaptive Biotechnologies.

IT 144

IT Cost-Benefit Statistics Consulting 144

Occam's Razor

SEPTEMBER 19, 2011

You need people with deep skills in Scientific Method , Design of Experiments , and Statistical Analysis. The team did the normal modeling to ensure that the results were statistically significant (large enough sample set, sufficient number of conversions in each variation). * ask for a raise. It is that simple. Okay, it is not simple.

Measurement 120

Measurement Advertising Testing Marketing 120

Sisense

JANUARY 21, 2020

This is an example of Simpon’s paradox , a statistical phenomenon in which a trend that is present when data is put into groups reverses or disappears when the data is combined. It’s time to introduce a new statistical term. So how do we get totally different results when breaking the data down by gender? See Kievit, Rogier, et al. ).

Testing 104

Testing Data-driven Risk Statistics 104

CIO Business Intelligence

JUNE 11, 2024

A 1958 Harvard Business Review article coined the term information technology, focusing their definition on rapidly processing large amounts of information, using statistical and mathematical methods in decision-making, and simulating higher order thinking through applications.

IT 136

IT Digital Transformation Broadcasting Business Objectives 136

Data Science and Beyond

JULY 22, 2018

Two years later, I published a post on my then-favourite definition of data science , as the intersection between software engineering and statistics. Like other authors, they argue that causal inference has been neglected by traditional statistics and some scientific disciplines. In a recent article , Hernán et al.

Data Science 79

Data Science Machine Learning Statistics Predictive Modeling 79

Occam's Razor

MARCH 23, 2021

This is very hard to do, we now have a proven seven-step experimentation process, with one of the coolest algorithms to pick matched-markets (normally the kiss of death of any large-scale geo experiment). What does the diminishing returns curve look like for TV GRPs for our company? More shouting is not really better – and it is expensive!

Analytics 133

Analytics Scorecard Strategy Testing 133

The Unofficial Google Data Science Blog

JANUARY 14, 2016

Unlike experimentation in some other areas, LSOS experiments present a surprising challenge to statisticians — even though we operate in the realm of “big data”, the statistical uncertainty in our experiments can be substantial. We must therefore maintain statistical rigor in quantifying experimental uncertainty.

Experimentation 42

Experimentation Statistics Metrics Measurement 42

The Unofficial Google Data Science Blog

APRIL 16, 2019

by MICHAEL FORTE Large-scale live experimentation is a big part of online product development. This means a small and growing product has to use experimentation differently and very carefully. This blog post is about experimentation in this regime. But these are not usually amenable to A/B experimentation.

Experimentation 69

Experimentation Sales Metrics Measurement 69

Occam's Razor

APRIL 8, 2013

Remember that the raw number is not the only important part, we would also measure statistical significance. Advanced Analytics Big Data Digital Analytics Web Analytics Web Insights Web Metrics actionable analytics business optimization experimentation and testing key performance indicators' The result? The graph is impressive, right?

Metrics 157

Metrics KPI Analytics Key Performance Indicator 157

DataRobot Blog

JANUARY 17, 2023

Not actually being a machine learning problem: Value-at-Risk modeling is the classic example here—VaR isn’t a prediction of anything, it’s a statistical summation of simulation results. As discussed, we massively accelerate that process of experimentation.

Machine Learning 87

Machine Learning Marketing Experimentation Data-driven 87

Occam's Razor

MARCH 23, 2010

Part of it is fueled by a vocal minority genuinely upset that 10 years on we are still not a statistically powered bunch doing complicated analysis that is shifting paradigms. If you don't have a robust experimentation program in your company you are going to die. Part of it fueled by some Consultants. Likely not.

Analytics 119

Analytics Consulting Metrics Experimentation 119

Octopai

MAY 2, 2022

Common elements of DataOps strategies include: Collaboration between data managers, developers and consumers A development environment conducive to experimentation Rapid deployment and iteration Automated testing Very low error rates. Issue detected?

Manufacturing 98

Manufacturing Testing Data Quality Dashboards 98

FineReport

DECEMBER 19, 2019

In addition, Jupyter Notebook is also an excellent interactive tool for data analysis and provides a convenient experimental platform for beginners. Pandas incorporates a large number of analysis function methods, as well as common statistical models and visualization processing. From Google. Data Analysis Libraries.

Knowledge Discovery 98

Knowledge Discovery Visualization Data mining Reporting 98

CIO Business Intelligence

JUNE 28, 2023

As Belcorp considered the difficulties it faced, the R&D division noted it could significantly expedite time-to-market and increase productivity in its product development process if it could shorten the timeframes of the experimental and testing phases in the R&D labs.

Digital Transformation 105

Digital Transformation Cost-Benefit Informatics Data mining 105

IBM Big Data Hub

MAY 20, 2024

As algorithm discovery and development matures and we expand our focus to real-world applications, commercial entities, too, are shifting from experimental proof-of-concepts toward utility-scale prototypes that will be integrated into their workflows.

Data Processing 94

Data Processing Optimization Experimentation Enterprise 94

O'Reilly on Data

MARCH 23, 2023

And it can look up an author and make statistical observations about their interests. ChatGPT offers users a paid account that costs $20/month, which is good enough for experimenters, though there is a limit on the number of requests you can make. Again, ChatGPT is predicting a response to your question.

IT 348

IT Modeling Testing Risk 348

Corinium

APRIL 25, 2019

For example auto insurance companies offering to capture real-time driving statistics from policy-holders’ cars to encourage and reward safe driving. And it’s become a hyper-competitive business, so enhancing customer service through data is critical for maintaining customer loyalty.

Insurance 150

Insurance Risk IoT Data-driven 150

CIO Business Intelligence

AUGUST 21, 2024

The flashpoint moment is that rather than being based on rules, statistics, and thresholds, now these systems are being imbued with the power of deep learning and deep reinforcement learning brought about by neural networks,” Mattmann says. But multiagent AI systems are still in the experimental stages, or used in very limited ways.

Risk 136

Risk Insurance Cost-Benefit Software 136