DataRobot

OCTOBER 19, 2021

Many available forecasts provide less than four weeks notice at the state and county level. Additionally, these forecasts often miss surges in community transmission until it is too late to change course. Traditional predictive models do not account for anomaly detection on data reporting issues (e.g.,

Forecasting 98

Forecasting Predictive Modeling Optimization Testing 98

Smarten

JUNE 26, 2018

This article provides a brief explanation of the ARIMA method of analytical forecasting. What is ARIMA Forecasting? Autoregressive Integrated Moving Average (ARIMA) predicts future values of a time series using a linear combination of its past values and a series of errors. p: to apply autoregressive model on series.

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Smarten

JUNE 29, 2018

This article looks at the ARIMAX Forecasting method of analysis and how it can be used for business analysis. What is ARIMAX Forecasting? This method is suitable for forecasting when data is stationary/non stationary, and multivariate with any type of data pattern, i.e., level/trend /seasonality/cyclicity. About Smarten.

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CIO Business Intelligence

JUNE 7, 2022

Data analytics draws from a range of disciplines — including computer programming, mathematics, and statistics — to perform analysis on data in an effort to describe, predict, and improve performance. Predictive analytics is often considered a type of “advanced analytics,” and frequently depends on machine learning and/or deep learning.

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IBM Big Data Hub

APRIL 28, 2022

To truly understand the data fabric’s value, let’s look at a retail supply chain use case where a data scientist wants to predict product back orders so that they can maintain optimal inventory levels and prevent customer churn. How does a data fabric impact the bottom line?

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Smarten

NOVEMBER 26, 2018

Predictive Analytics used to involve a crystal ball but, today, there are other options and they are more widely accepted in the business community! And, with Assisted Predictive Modeling , your business users can leverage sophisticated tools, algorithms and techniques in a simple, intuitive environment to predict future results.

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IBM Big Data Hub

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

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Smarten

JANUARY 21, 2019

Time Series Forecasting. Holt-Winters Forecasting. ARIMA Forecasting. Chi Square Test. ARIMAX Forecasting. Paired Sample T Test. Dependent Sample T-Test. Independent Samples T Test. Discover how easy it is to capitalize on Augmented Analytics and Predictive Modeling !

Analytics 40

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DataRobot

JUNE 4, 2021

As new algorithms prove their merit, they are incorporated into DataRobot’s algorithm repository, and the platform continues to adapt and evolve even after models are deployed through a concept called continuous learning. Forecasting In-Store Foot Traffic. Here, we have a model that predicts foot traffic for a chain of coffee shops.

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Smarten

SEPTEMBER 26, 2018

How Can My Business Use Assisted Predictive Modeling to Optimize Resources? There was a time, not so long ago, when predictive analysis, business forecasting and planning for results involved guesswork and lots of unscientific review of historical data.

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Smarten

APRIL 17, 2018

How Can Assistive Predictive Modeling Help My Business Users? If you are wondering how and why predictive analytics software has expanded into the self-serve business user market, the reason is simple. Assisted Predictive Modeling can help your business achieve its goals.

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Smarten

MAY 17, 2019

Predictive analytics can help the business to understand online buying behavior, and when, where and how to serve ads, market products and offer discounts or other incentives. Predictive analytics will help you optimize your marketing budget and improve brand loyalty. Predictive Analytics Using External Data. Customer Targeting.

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IBM Big Data Hub

FEBRUARY 14, 2024

Other uses include Netflix offering viewing recommendations powered by models that process data sets collected from viewing history; LinkedIn uses ML to filter items in a newsfeed, making employment recommendations and suggestions on who to connect with; and Spotify uses ML models to generate its song recommendations.

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IBM Big Data Hub

JULY 6, 2023

Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming. Because data analysts often build machine learning models, programming and AI knowledge are also valuable. Deep learning algorithms are neural networks modeled after the human brain.

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Smarten

JUNE 10, 2022

Recent studies have focused on the trends in business intelligence and augmented analytics, predicting that businesses will grow analytics within the enterprise with: Augmented Analytics to enable non-technical business users to create sophisticated data models. Assisted Predictive Modeling.

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Smarten

AUGUST 21, 2019

Assisted Predictive Modeling – These tools enable the average business user to leverage sophisticated predictive algorithms without requiring statistical or data science skills. Users can highlight trends and patterns, test hypotheses and theories to reduce business risk, and easily predict and forecast results.

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Smarten

JANUARY 31, 2019

Put simply, business Intelligence uses historical data to reveal where the business has been, and managers can use this data to predict competitive response and discover what is changing in customer buying behavior and in sales. How is Advanced Analytics Different from Business Intelligence?

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IBM Big Data Hub

OCTOBER 16, 2023

ML also helps businesses forecast and decrease customer churn (the rate at which a company loses customers), a widespread use of big data. Reinforcement learning uses ML to train models to identify and respond to cyberattacks and detect intrusions. Spotify uses ML models to generate its song recommendations.

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DataRobot Blog

DECEMBER 15, 2022

AI-powered Time Series Forecasting may be the most powerful aspect of machine learning available today. Working from datasets you already have, a Time Series Forecasting model can help you better understand seasonality and cyclical behavior and make future-facing decisions, such as reducing inventory or staff planning.

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Smarten

JUNE 20, 2018

The business can use this information for forecasting and planning, and to test theories and strategies. In prediction, the objective is to “model” all the components to some trend patterns to the point that the only component that remains unexplained is the random component. Stationary/Stationarity.

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Birst BI

AUGUST 23, 2018

For example, there are a plethora of software tools available to automatically develop predictive models from relational data, and according to Gartner, “By 2020, more than 40% of data science tasks will be automated, resulting in increased productivity and broader usage by citizen data scientists.” [1]

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Smarten

JUNE 29, 2018

Multiple linear regression models are useful in helping an enterprise to consider the impact of multiple independent predictors and variables on a dependent variable, and can be beneficial for forecasting and predicting results. About Smarten.

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Smarten

JUNE 27, 2018

To explore this technique further, let’s conduct the SVM classification using the following variables: Here we see a sample output for the actual versus predicted outcome. The prediction accuracy is useful criterion for assessing the model performance. Model with prediction accuracy >= 70% is useful.

Business Analytics 40

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Smarten

NOVEMBER 3, 2017

Empowers business users with access to meaningful data to test theories and hypotheses without the assistance of data scientists or IT staff. Smart Visualization – Smart Data Visualization, suggests the best options for visualizing and plotting for a particular set or type of data, based on the nature, dimensions and trend of data.

Analytics 40

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Smarten

JUNE 29, 2018

Weather Forecasting – Based on temperature, humidity, pressure etc., an organization can predict if it will be rainy/sunny/windy tomorrow. a business can predict the likelihood of fraud. It is useful for making predictions and forecasting data based on historical results. About Smarten.

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Smarten

JUNE 29, 2018

The KNN Classification algorithm is useful in determining probable outcome and results and in forecasting and predicting results, given the existence of multiple variables. About Smarten.

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The Unofficial Google Data Science Blog

DECEMBER 4, 2019

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. Our team does a lot of forecasting. It also owns Google’s internal time series forecasting platform described in an earlier blog post.

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Forecasting Data Science Statistics Uncertainty 113

Cloudera

SEPTEMBER 7, 2023

With the emergence of new creative AI algorithms like large language models (LLM) fromOpenAI’s ChatGPT, Google’s Bard, Meta’s LLaMa, and Bloomberg’s BloombergGPT—awareness, interest and adoption of AI use cases across industries is at an all time high. The reality of LLMs and other “narrow” AI technologies is that none of them is turn-key.

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Insurance Risk Data-driven Modeling 79

DataRobot

NOVEMBER 15, 2021

DataRobot AI Cloud on AWS enables organizations across the banking and healthcare industry to easily build, deploy, and monitor machine learning models that yield actionable insights and ROI. DataRobot & Palantir Foundry Demand Forecasting Solution. Find out more.

Manufacturing 52

Manufacturing Forecasting Machine Learning Data-driven 52

Domino Data Lab

AUGUST 22, 2019

The excerpt covers how to create word vectors and utilize them as an input into a deep learning model. While the field of computational linguistics, or Natural Language Processing (NLP), has been around for decades, the increased interest in and use of deep learning models has also propelled applications of NLP forward within industry.

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Smarten

JULY 10, 2018

Use Case(s): Weather Forecasting, Fraud Analysis and more. Independent Samples T Test: What is the Independent Samples T Test Method of Analysis and How Can it Benefit an Organization? Paired Sample T Test: What is the Paired Sample T Test and How is it Beneficial to Business Analysis?

Analytics 40

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IBM Big Data Hub

JULY 5, 2023

It allows the company to run tests and predict performance based on simulations. With a good digital twin, it’s possible to predict how an asset will perform under certain conditions and what it’s projected lifespan will be. A digital twin is a virtual representation of an asset that a company intends to purchase.

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Insight

FEBRUARY 19, 2020

Photo by Roberto Nickson on Unsplash Much effort has been spent understanding and forecasting the success of movies (e.g., Arthur de Vany’s Hollywood Economics and Kaggle’s recent box office prediction challenge ) and current attempts are using increasingly sophisticated techniques. The solid line shows the y=x line for comparison.

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Rocket-Powered Data Science

SEPTEMBER 20, 2021

The data scientists need to find the right data as inputs for their models — they also need a place to write-back the outputs of their models to the data repository for other users to access. The BI team may be focused on KPIs, forecasts, trends, and decision-support insights. That’s data democratization.

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DataRobot Blog

JUNE 24, 2022

In addition, traditional analytical approaches are not flexible enough in generating alternative scenarios that allow investment analysts to test market shifts or to compare predictive-model outputs to the forecasts of traditional sources of market information. Forecasting the Real Estate Market Using DataRobot.

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Smarten

DECEMBER 5, 2022

Self-serve assisted predictive modeling provides recommendations and suggestions based on data volume, type and other parameters, so users will be directed to the appropriate analytical techniques and receive clear, concise results that are easy to understand and apply for confident decisions. Paired Sample T Test.

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DataRobot

JANUARY 20, 2022

The UK’s National Health Service (NHS) will be legally organized into Integrated Care Systems from April 1, 2022, and this convergence sets a mandate for an acceleration of data integration, intelligence creation, and forecasting across regions. Looking forward through data. Grasping the digital opportunity.

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