IBM Big Data Hub

SEPTEMBER 19, 2023

Data science is an area of expertise that combines many disciplines such as mathematics, computer science, software engineering and statistics. Many functions of data analytics—such as making predictions—are built on machine learning algorithms and models that are developed by data scientists.

Data Science 83

Data Science Data Analytics Prescriptive Analytics Analytics 83

Smart Data Collective

OCTOBER 8, 2021

Modern machine learning and back-testing; how quant hedge funds use it. Similarly, hedge funds often use modern machine learning and back-testing to analyze their quant models. Here, the models get tested using historical data to evaluate their profitability. Mathematical Model-based Strategies.

Machine Learning 113

Machine Learning Testing Strategy Modeling 113

O'Reilly on Data

JULY 28, 2020

Product Managers are responsible for the successful development, testing, release, and adoption of a product, and for leading the team that implements those milestones. You must detect when the model has become stale, and retrain it as necessary. The Core Responsibilities of the AI Product Manager. The AI Product Development Process.

Marketing 362

Marketing Experimentation Metrics Testing 362

Smarten

JUNE 26, 2018

This article provides a brief explanation of the ARIMA method of analytical forecasting. What is ARIMA Forecasting? This analytical forecasting method is suitable for instances when data is stationary/non stationary and is univariate, with any type of data pattern, i.e., level/trend/seasonality/cyclicity. About Smarten.

Forecasting 40

Forecasting Enterprise IT Sales 40

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.

Forecasting 40

Forecasting Enterprise IT Business Intelligence 40

CIO Business Intelligence

JUNE 14, 2023

The certification focuses on the seven domains of the analytics process: business problem framing, analytics problem framing, data, methodology selection, model building, deployment, and lifecycle management. Organization: AWS Price: US$300 How to prepare: Amazon offers free exam guides, sample questions, practice tests, and digital training.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

Smarten

MAY 31, 2022

When combined with Citizen Data Scientist initiatives, the adoption and use of predictive modeling and forecasting techniques can be a boon to any enterprise. Team members who have access to augmented analytics and assisted predictive modeling can plan better, predict more accurately and dependably meet goals and objectives.

Predictive Analytics 67

Predictive Analytics Analytics Predictive Modeling Prescriptive Analytics 67

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. Ultimately, data science is used in defining new business problems that machine learning techniques and statistical analysis can then help solve.

Machine Learning 58

Machine Learning Data Science Statistics Deep Learning 58

Juice Analytics

APRIL 17, 2020

He goes on to clarify by saying that some estimate that 80% of the cases don’t get tested, so we don’t actually know the real number of cases, but it’s likely very much higher. Forecasts are not Predictions (But they’re still useful.) And forecast modelers know how not only to create those, but also how to interpret them.

Forecasting 85

Forecasting Snapshot Dashboards Uncertainty 85

Smart Data Collective

MARCH 8, 2021

According to a forecast by IDC and Seagate Technology, the global data sphere will grow more than fivefold in the next seven years. Thanks to the availability of comparative data for practically every type/model of a vehicle, fleet managers can plan maintenance activities based on certain knowledge. Fuel Management.

Big Data 143

Big Data Management Predictive Analytics Statistics 143

FineReport

MARCH 24, 2024

Predictive analytics: Forecasting likely outcomes based on patterns and trends to facilitate proactive decision-making. Data analysts contribute value to organizations by uncovering trends, patterns, and insights through data gathering, cleaning, and statistical analysis.

Statistics 52

Statistics Data mining Visualization Reporting 52

CIO Business Intelligence

AUGUST 24, 2023

And with large language models (LLM), data governance is in its infancy. Retraining, deployment, operations, testing—a lot of these features just aren’t available yet.” That can include learning how to verify that correct controls are in place, models are isolated, and they’re appropriately used, he says. AI is a black box.

Uncertainty 98

Uncertainty Risk Testing Enterprise 98

Smarten

JANUARY 21, 2019

Time Series Forecasting. Holt-Winters Forecasting. Descriptive Statistics. ARIMA Forecasting. Chi Square Test. ARIMAX Forecasting. Paired Sample T Test. Dependent Sample T-Test. Independent Samples T Test. Consider the myriad of techniques used by data scientists and analysts!

Analytics 40

Analytics Predictive Modeling Forecasting Testing 40

Smart Data Collective

AUGUST 19, 2021

The statistics don’t lie either. Product testing and progress. Through product testing and trialing, it can help properly access the product and ultimately, it’s chances of success when the product launches. From the product’s concept, it can help developers test what’s needed in order to perfect every part of the product.

Analytics 126

Analytics Cost-Benefit Software Testing 126

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.

Analytics 51

Analytics Predictive Modeling Visualization Statistics 51

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.

Forecasting 40

Forecasting Statistics Business Intelligence Predictive Modeling 40

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] Develop and test a model in R Studio.

Machine Learning 73

Machine Learning Data Science Testing Metrics 73

Smarten

JUNE 29, 2018

Multiple Linear Regression is a statistical technique that is designed to explore the relationship between two or more variables (X, and Y). All of these tools are designed for business users with average skills and require no special skills or knowledge of statistical analysis or support from IT or data scientists. About Smarten.

Business Analysis 40

Business Analysis IT Sales Statistics 40

O'Reilly on Data

NOVEMBER 28, 2023

And everyone has opinions about how these language models and art generation programs are going to change the nature of work, usher in the singularity, or perhaps even doom the human race. 16% of respondents working with AI are using open source models. A few have even tried out Bard or Claude, or run LLaMA 1 on their laptop.

Enterprise 271

Enterprise Modeling Testing Reporting 271

Smarten

JUNE 27, 2018

The prediction accuracy is useful criterion for assessing the model performance. Model with prediction accuracy >= 70% is useful. Weather Forecasting – Based on temperature, humidity, pressure etc. Classification Accuracy (35+ 70) / (35+70+4+4) = 92%. Classification Error = 100- Accuracy = 8%.

Business Analytics 40

Business Analytics Analytics IT Business Intelligence 40

Smarten

JUNE 29, 2018

Weather Forecasting – Based on temperature, humidity, pressure etc., It is useful for making predictions and forecasting data based on historical results. For numerical variable, normal distribution is assumed which is a strong assumption. How Can Naïve Bayes Be Used for Enterprise Analysis? About Smarten.

Enterprise 40

Enterprise IT Business Intelligence Forecasting 40

Domino Data Lab

AUGUST 9, 2021

For a model-driven enterprise, having access to the appropriate tools can mean the difference between operating at a loss with a string of late projects lingering ahead of you or exceeding productivity and profitability forecasts. What Are Modeling Tools? Importance of Modeling Tools. Types of Modeling Tools.

Modeling 111

Modeling Deep Learning Machine Learning Statistics 111

Rita Sallam

APRIL 2, 2023

Interpretation of our machine learning model suggests buying $50k in building coverage and $100k in warehouse content coverage, as the latter significantly boosts predicted flood claim payouts. Pattern-basis can also consist of gradual drift and shift of workload patterns and this can be built into a predictive efficiency model.

Optimization 52

Optimization Machine Learning Insurance Risk 52

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.

Forecasting 113

Forecasting Data Science Statistics Uncertainty 113

Smarten

NOVEMBER 22, 2017

Self-Serve Advanced Analytics provides a roadmap to guide you through a maze of organizational data with tools and models that will bring together data from disparate sources and enable sophisticated yet simple analytics. These tools allow the enterprise to establish and monitor key metrics and to objectively assess results.

Analytics 40

Analytics IT Business Intelligence Visualization 40

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.

Enterprise 40

Enterprise Business Intelligence Predictive Modeling Statistics 40

CIO Business Intelligence

SEPTEMBER 7, 2023

The first is forecasting, where AI is used to make predictions about downstream demand or upstream shortages. In the meantime, many companies continue to reap the benefits of improved forecasting and inspection. Some of the challenges Amcor faces in manufacturing have to do with accurate forecasting and adapting to changing demand.

Management 138

Management Forecasting Manufacturing Cost-Benefit 138

O'Reilly on Data

MAY 27, 2020

Under school district policy, each of Audrey’s eleven- and twelve-year old students is tested at least three times a year to determine his or her Lexile, a number between 200 and 1,700 that reflects how well the student can read. They test each student’s grasp of a particular sentence or paragraph—but not of a whole story.

Risk 355

Risk Testing Reporting Measurement 355

FineReport

JULY 18, 2022

It provides you with functions like adding columns, grouping statistics, filtering, sorting, merging up and down, right and left, and so on, so that you can process data based on your own needs. R language is also an excellent programming language focusing on statistical analysis and graphics. SAS Forecasting. From KNIME.

Forecasting 52

Forecasting Dashboards Visualization Statistics 52

DataRobot Blog

APRIL 4, 2022

MMM stands for Marketing Mix Model and it is one of the oldest and most well-established techniques to measure the sales impact of marketing activity statistically. As with any type of statistical model, data is key and GIGO (“Garbage In, Garbage Out”) principle definitely applies. Classical Modeling Considerations.

Machine Learning 52

Machine Learning Sales Measurement ROI 52

datapine

NOVEMBER 15, 2022

Of course, the indicators tracked at this stage will depend on the audience and the business model. Just like with the acquisition stage, the desired actions will depend on the business model. Of course, as in the other stages of this framework, the metrics tracked here will depend on the business model.

Metrics 141

Metrics KPI Measurement Dashboards 141

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.

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

by TAMAN NARAYAN & SEN ZHAO A data scientist is often in possession of domain knowledge which she cannot easily apply to the structure of the model. On the one hand, basic statistical models (e.g. On the other hand, sophisticated machine learning models are flexible in their form but not easy to control.

Machine Learning 108

Machine Learning Deep Learning Modeling Interactive 108

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

Analytics Forecasting Statistics Sales 40

Sisense

AUGUST 21, 2020

From Forecast to Trends to natural language querying, we are completely transparent about the technology behind and the statistical characteristics of the output. Gartner: “By 2023, more than 33% of large organizations will have analysts practicing decision intelligence, including decision modeling.”. “It

Analytics 112

Analytics Machine Learning Dashboards Visualization 112

BI-Survey

FEBRUARY 14, 2022

Although many initiatives have already been realized around planning and forecasting in recent months, too many were just short-term fixes that did not bring the significant and lasting improvements required. This study examined the contribution modern planning and forecasting can make to corporate management. Are there better methods?

Forecasting 52

Forecasting Uncertainty Measurement Software 52

Smart Data Collective

OCTOBER 16, 2022

As a matter of fact, worldwide spending on public cloud services is forecasted to reach around $494.7 An ideal time to consider this architecture is while building an ecosystem for testing and development. Make an informed decision based on various cloud architect solutions, market research, and data statistics.

Consulting 107

Consulting Software Statistics Manufacturing 107