Cloudera

OCTOBER 27, 2020

Our goal is to take the incredible data science and machine learning research developments we see emerging from academia and large industrial labs, and bridge the gap to products and processes that are useful to practitioners working across industries. While point predictions limit us to asking “what is the demand forecast for Tuesday?”

Deep Learning 59

Deep Learning Machine Learning Forecasting Uncertainty 59

Sisense

SEPTEMBER 9, 2019

If you lack a data science team, integrating BigSquid with your open-platform BI tool is a powerful way to achieve the horsepower of data science while maintaining the ease of use that the average business user requires. And we could easily visualize how a fix could impact our warranty claim forecast.

Predictive Analytics 75

Predictive Analytics Predictive Modeling Forecasting Data-driven 75

The Unofficial Google Data Science Blog

DECEMBER 4, 2019

by THOMAS OLAVSON Thomas leads a team at Google called "Operations Data Science" that helps Google scale its infrastructure capacity optimally. ln this post he describes where and how having “humans in the loop” in forecasting makes sense, and reflects on past failures and successes that have led him to this perspective.

Forecasting 113

Forecasting Data Science Statistics Uncertainty 113

bridgei2i

JUNE 3, 2020

Consumers feel threatened by the prolonged uncertainty, not having had to deal with anything like it, in their lives. This enhanced collaboration can also provide opportunities to gather granular data to understand various consumer segments, something CTD companies haven’t been able to do too well in the past.

Manufacturing 52

Manufacturing Forecasting Uncertainty Digital Transformation 52

Jet Global

MARCH 2, 2021

Modern BI tools are generally geared toward data science and visualization. Considering the recent volatility of the economic environment, planning and forecasting is becoming more important than ever before. Extending Yardi’s Capabilities.

Reporting 98

Reporting Slice and Dice Finance Operational Reporting 98

Domino Data Lab

JUNE 2, 2019

Co-chair Paco Nathan provides highlights of Rev 2 , a data science leaders summit. We held Rev 2 May 23-24 in NYC, as the place where “data science leaders and their teams come to learn from each other.” If you lead a data science team/org, DM me and I’ll send you an invite to data-head.slack.com ”.

Data-driven 110

Data-driven Data Science Machine Learning Modeling 110

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. Introduction Time series data appear in a surprising number of applications, ranging from business, to the physical and social sciences, to health, medicine, and engineering. by STEVEN L.

Forecasting 64

Forecasting Statistics Modeling Software 64

Sisense

APRIL 13, 2020

If data science is your jam, there are so many exciting new developments in AI, machine learning, natural language processing, and graph databases that you could keep busy reading for days on end. For me, the takeaway is the need to prepare those critical things to face uncertainty in the current market.”.

Uncertainty 83

Uncertainty Marketing Digital Transformation Forecasting 83

The Unofficial Google Data Science Blog

APRIL 19, 2021

To explain, let’s borrow a quote from Nate Silver’s The Signal and the Noise : One of the most important tests of a forecast — I would argue that it is the single most important one — is called calibration. If, over the long run, it really did rain about 40 percent of the time, that means your forecasts were well calibrated.

Modeling 122

Modeling IT Metrics Testing 122

Insight

FEBRUARY 19, 2020

Using variability in machine learning predictions as a proxy for risk can help studio executives and producers decide whether or not to green light a film project Photo by Kyle Smith on Unsplash Originally posted on Toward Data Science. Are you interested in working on high-impact projects and transitioning to a career in data?

Risk 67

Risk ROI Modeling Metrics 67

Smarten

JULY 18, 2022

By incorporating analytics into day-to-day activities and allowing access for business users, the business can encourage the transition from business user to Citizen Data Scientist and create a comprehensive system of analytics with governance and collaboration to ensure security, appropriate access, mobile use and fact-based decision-making.

Uncertainty 52

Uncertainty Predictive Analytics Forecasting Analytics 52