Smart Data Collective

JULY 1, 2023

Image annotation is the act of labeling images for AI and machine learning models. This helps train the AI model by assigning classes to different entities in an image. Improving annotation quality is crucial for various tasks, including data labeling for machine learning models, document categorization, sentiment analysis, and more.

Metrics 64

Metrics Machine Learning Uncertainty Deep Learning 64

O'Reilly on Data

OCTOBER 13, 2020

Similarly, in “ Building Machine Learning Powered Applications: Going from Idea to Product ,” Emmanuel Ameisen states: “Indeed, exposing a model to users in production comes with a set of challenges that mirrors the ones that come with debugging a model.”.

Management 244

Management Metrics Machine Learning Modeling 244

CIO Business Intelligence

SEPTEMBER 20, 2023

They are afraid of failure and the uncertainty of knowledge work, and so that’s stressful. Agile is an amazing risk management tool for managing uncertainty, but that’s not always obvious.” The key is recognizing that planning must be an agile discipline, not a standalone activity performed independently of agile teams.

Digital Transformation 125

Digital Transformation Uncertainty Metrics Business Objectives 125

The Unofficial Google Data Science Blog

APRIL 19, 2021

by LEE RICHARDSON & TAYLOR POSPISIL Calibrated models make probabilistic predictions that match real world probabilities. While calibration seems like a straightforward and perhaps trivial property, miscalibrated models are actually quite common. Why calibration matters What are the consequences of miscalibrated models?

Modeling 122

Modeling IT Metrics Testing 122

The Unofficial Google Data Science Blog

DECEMBER 4, 2019

Others argue that there will still be a unique role for the data scientist to deal with ambiguous objectives, messy data, and knowing the limits of any given model. This classification is based on the purpose, horizon, update frequency and uncertainty of the forecast.

Forecasting 113

Forecasting Data Science Statistics Uncertainty 113

Sisense

MARCH 26, 2020

To effectively identify what measures need to be taken, analytics can help to summarize and predict how companies should evolve to survive in a challenging environment. Now is the time to apply the full force of business intelligence used by analytics teams to help navigate growing uncertainty. Making smarter staffing decisions.

Management 91

Management Cost-Benefit Uncertainty Digital Transformation 91

AWS Big Data

AUGUST 7, 2023

Forecasting acts as a planning tool to help enterprises prepare for the uncertainty that can occur in the future. Amazon Redshift ML makes it easy for data analysts and database developers to create, train, and apply machine learning (ML) models using familiar SQL commands in Amazon Redshift. You pay only the associated Forecast costs.

Forecasting 86

Forecasting Data Warehouse Machine Learning Modeling 86

Insight

FEBRUARY 19, 2020

My goal here is not to improve upon the current prediction algorithms but rather to describe a model I devised, called ReelRisk , that uses random resampling to generate a range of predictions which can then be used as a risk assessment tool to determine early on whether to fund a movie.

Risk 67

Risk ROI Modeling Metrics 67

CIO Business Intelligence

JANUARY 4, 2023

Here are the shifts we noted: Delivery Models : Moving from an almost strictly on-premises systems approach (with some remote access services), HPC is embracing remote delivery models. Due to the rapid growth in data sizes, there’s an increased need for HPC solutions that can run large training models.

Cost-Benefit 59

Cost-Benefit Machine Learning Modeling Uncertainty 59

CIO Business Intelligence

JULY 7, 2023

This module validates your ability to measure, assess, and develop the Service Desk practice capability using the ITIL Maturity Model. It covers challenges around volatility, uncertainty, complexity, and ambiguity (VUCA) and how to conduct a full cost benefit analysis to identify potential risks and opportunities.

Cost-Benefit 97

Cost-Benefit Strategy Management Uncertainty 97

Domino Data Lab

JUNE 2, 2019

We had data science leaders presenting about lessons learned while leading data science teams, covering key aspects including scalability, being model-driven, being model-informed, and how to shape the company culture effectively. Data science leadership: importance of being model-driven and model-informed.

Data-driven 110

Data-driven Data Science Machine Learning Modeling 110

Domino Data Lab

JUNE 23, 2019

Ensure that product managers work on projects that matter to the business and/or are aligned to strategic company metrics. These measurement-obsessed companies have an advantage when it comes to AI. Another pattern that I’ve seen in good PMs is that they’re very metric-driven. You really have to just go through it.

Management 110

Management Machine Learning Experimentation Metrics 110

Peter James Thomas

AUGUST 12, 2018

This piece was prompted by both Olaf’s question and a recent article by my friend Neil Raden on his Silicon Angle blog, Performance management: Can you really manage what you measure? It is hard to account for such tweaking in measurement systems. Pertinence and fidelity of metrics developed from Data.

Metrics 49

Metrics Statistics Data Quality Measurement 49

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 41

Experimentation Statistics Metrics Measurement 41

The Unofficial Google Data Science Blog

APRIL 16, 2019

Modern products often don't start with set-in-stone business models because starting and scaling costs are low. Such decisions involve an actual hypothesis test on specific metrics (e.g. The metrics to measure the impact of the change might not yet be established. Wonders of the internet (and VC funding)!

Experimentation 68

Experimentation Sales Metrics Measurement 68

bridgei2i

JULY 8, 2020

This is probably the first time ever that we are witnessing a demand, a supply, and also a resource uncertainty. And if you’re a banker or an insurer, you’re probably busy figuring out how to measure these risks, mobilize these resources, and fund capital that’s going to provide strong growth. These are strange times.

Digital Transformation 132

Digital Transformation Enterprise Insurance Risk 132

The Unofficial Google Data Science Blog

AUGUST 27, 2019

Of course, any mistakes by the reviewers would propagate to the accuracy of the metrics, and the metrics calculation should take into account human errors. If we could separate bad videos from good videos perfectly, we could simply calculate the metrics directly without sampling. The missing verdicts create two problems.

Metrics 98

Metrics Statistics Uncertainty Optimization 98

Jet Global

SEPTEMBER 10, 2020

Living through periods of rapid upheaval and uncertainty, like the recent pandemic, forces us to adapt quickly to new working practices. One area that often goes overlooked is the value that can be achieved from the application of consolidated KPIs to measure major indicators. Addressing Long-Lasting Changes.

Forecasting 52

Forecasting Finance Uncertainty Sales 52

DataKitchen

SEPTEMBER 21, 2023

The uncertainty of not knowing where data issues will crop up next and the tiresome game of ‘who’s to blame’ when pinpointing the failure. Moreover, advanced metrics like Percentage Regional Sales Growth can provide nuanced insights into business performance. One of the primary sources of tension?

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

The Unofficial Google Data Science Blog

MAY 31, 2016

It is important that we can measure the effect of these offline conversions as well. Panel studies make it possible to measure user behavior along with the exposure to ads and other online elements. Let's take a look at larger groups of individuals whose aggregate behavior we can measure. days or weeks).

Advertising 42

Advertising Testing Sales Statistics 42

The Unofficial Google Data Science Blog

FEBRUARY 29, 2016

The result is that experimenters can’t afford to be sloppy about quantifying uncertainty. These typically result in smaller estimation uncertainty and tighter interval estimates. Variance reduction through conditioning Suppose, as an LSOS experimenter, you find that your key metric varies a lot by country and time of day.

Experimentation 40

Experimentation Metrics Statistics Measurement 40

Occam's Razor

APRIL 15, 2019

A decade ago, data people delivered a lot less bad news because so little could be measured with any degree of confidence. In 2019, we can measure the crap out of so much. Bubble Kings most commonly reside in organizations where there is little to no accountability (or misplaced accountability, ex: celebration of vanity metrics).

Measurement 79

Measurement Strategy Data Processing Uncertainty 79

CIO Business Intelligence

JUNE 8, 2022

Digital disruption, global pandemic, geopolitical crises, economic uncertainty — volatility has thrown into question time-honored beliefs about how best to lead IT. Thriving amid uncertainty means staying flexible, he argues. . Demand transparency on everything — especially on metrics — and be transparent back.

IT 133

IT Cost-Benefit Uncertainty Digital Transformation 133

The Unofficial Google Data Science Blog

OCTOBER 21, 2015

It is important to make clear distinctions among each of these, and to advance the state of knowledge through concerted observation, modeling and experimentation. Note also that this account does not involve ambiguity due to statistical uncertainty. This is very much the work of a scientist.

Slice and Dice 45

Slice and Dice Experimentation Data-driven Data Science 45

Jet Global

NOVEMBER 10, 2021

Enterprise planning is transformational; it’s not just a new and improved method for business planning, but rather, a seed for cultural change that aligns organizational resources around a common set of goals, objectives, and metrics. At insightsoftware, we provide tools that facilitate agile enterprise planning and modeling.

Enterprise 52

Enterprise Recreation/Entertainment Finance Reporting 52