Domino Data Lab

JULY 28, 2021

There are many software packages that allow anyone to build a predictive model, but without expertise in math and statistics, a practitioner runs the risk of creating a faulty, unethical, and even possibly illegal data science application. All models are not made equal. Computer Science Skills.

Data Science 110

Data Science Statistics Recreation/Entertainment Predictive Analytics 110

AWS Big Data

NOVEMBER 10, 2023

The business opportunity There are 19 predictive models in scope for utilizing 93 features built with AWS Glue across Capitec’s Retail Credit divisions. This interface allows them to access and integrate the necessary data from the EDW into the data pipelines, enabling efficient development and testing of features.

Data Processing 93

Data Processing Data Lake Data Warehouse Optimization 93

Business Over Broadway

SEPTEMBER 27, 2018

Figure 1 includes a good illustration of different data sets and how they fall along these two size-related dimensions (For the interested reader, check out the figure in an interactive graphic ). genetic counseling, genetic testing). Machine Learning and Predictive Modeling of Customer Churn. segmentation on steroids).

Machine Learning 76

Machine Learning Data Integration Marketing Predictive Modeling 76

Juice Analytics

MARCH 11, 2021

Predictive models to take descriptive data and attempt to tell the future. She crafts the interface and interactions to make the data intuitive. Front-end Application Developer The Front-end Application Developer's role is all about building interface elements, interactions, and data visualizations. Just kidding!

Predictive Modeling 128

Predictive Modeling Visualization Reporting Interactive 128

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.

Business Intelligence 40

Business Intelligence Analytics Predictive Modeling Forecasting 40

CIO Business Intelligence

APRIL 25, 2022

It culminates with a capstone project that requires creating a machine learning model. The bootcamps are designed and taught by industry practitioners and cover Python, algorithms, linear regression, machine learning, NLP, databases, interactive data visualization, and more. Data Science Dojo.

Data Science 145

Data Science Machine Learning Deep Learning Statistics 145

DataKitchen

SEPTEMBER 21, 2023

In the context of Data in Place, validating data quality automatically with Business Domain Tests is imperative for ensuring the trustworthiness of your data assets. Running these automated tests as part of your DataOps and Data Observability strategy allows for early detection of discrepancies or errors.

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

Birst BI

OCTOBER 30, 2018

The credit scores generated by the predictive model are then used to approve or deny credit cards or loans to customers. A well-designed credit scoring algorithm will properly predict both the low- and high-risk customers. Integrate the data sources of the various behavioral attributes into a functional data model.

Predictive Analytics 73

Predictive Analytics Descriptive Analytics Analytics Metrics 73

O'Reilly on Data

SEPTEMBER 19, 2023

” Each step has been a twist on “what if we could write code to interact with a tamper-resistant ledger in real-time?” Stage 2: Machine learning models Hadoop could kind of do ML, thanks to third-party tools. ” Most recently, I’ve been thinking about this in terms of the space we currently call “AI.”

Machine Learning 256

Machine Learning Testing Modeling Cost-Benefit 256

Smarten

APRIL 19, 2024

OpenAI – Azure OpenAI as the foundational entity for creating GPT models and is based on Large Language Models (LLM). GPT – Is based on a Large Language Model (LLM). Benefits include customized and optimized models, data, parameters and tuning. Open AI was developed by Microsoft.

Analytics 57

Analytics Predictive Modeling KPI Machine Learning 57

Insight

AUGUST 5, 2020

While most of these signals are implicitly communicated during human-to-human interaction, we do not have a method for quantifying feeling and mood through individual behavioral signals expressed on the digital platform. Prediction models An Exploratory Data Analysis showed improved performance was dependent on gender and emotion.

Predictive Modeling 98

Predictive Modeling Statistics Modeling Measurement 98

Domino Data Lab

NOVEMBER 17, 2020

Predictive models fit to noise approach 100% accuracy. For example, it’s impossible to know if your predictive model is accurate because it is fitting important variables or noise. Understanding the meaning and interactions of 500 coefficients is not possible. Pairwise distances between points become the same.

Statistics 131

Statistics Measurement Testing Predictive Modeling 131

O'Reilly on Data

SEPTEMBER 15, 2020

This in turn would increase the platform’s value for users and thus increase engagement, which would result in more eyes to see and interact with ads, which would mean better ROI on ad spend for customers, which would then achieve the goal of increased revenue and customer retention (for business stakeholders).

Cost-Benefit 300

Cost-Benefit Advertising ROI Machine Learning 300

CIO Business Intelligence

AUGUST 15, 2023

Shamim Mohammad, CIO, CarMax CarMax That volume created a Sisyphean task for the company’s content writers, as they struggled to provide up-to-date information by make, model, and year for each vehicle in the company’s constantly changing inventory. They turned to artificial intelligence to help.

IT 92

IT Manufacturing IoT Cost-Benefit 92

Alation

APRIL 14, 2022

And, as organizations progress and grow, “data drift” starts to impact data usage, models, and your business. Supports the ability to interact with the actual data and perform analysis on it. Automatic sampling to test transformation. Model Drift. Models too, can drift and transform over time. Pattern Matching.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

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

DataRobot Blog

JANUARY 10, 2023

Most, if not all, machine learning (ML) models in production today were born in notebooks before they were put into production. In the image above, we have imported the DataRobot Python client and kickstarted model training using Autopilot, the DataRobot automated machine learning capability. Did you notice?

Experimentation 52

Experimentation Machine Learning Data Science Modeling 52

The Unofficial Google Data Science Blog

MARCH 31, 2016

KUEHNEL, and ALI NASIRI AMINI In this post, we give a brief introduction to random effects models, and discuss some of their uses. Through simulation we illustrate issues with model fitting techniques that depend on matrix factorization. Random effects models are a useful tool for both exploratory analyses and prediction problems.

Modeling 40

Modeling Statistics Advertising Testing 40

Domino Data Lab

AUGUST 20, 2019

Feature engineering is useful for data scientists when assessing tradeoff decisions regarding the impact of their ML models. It is a framework for approaching ML as well as providing techniques for extracting features from raw data that can be used within the models. We can also modify the features before we start the modeling process.

Testing 68

Testing Modeling Interactive Measurement 68

Domino Data Lab

OCTOBER 23, 2019

This chapter will explore the numbers behind the numbers using ML and then creating an API to serve out the ML model. This means covering details like setting up your environment, deployment, and monitoring, in addition to creating models on clean data. You can add a Makefile command test that will run all of your notebooks by issuing.

Statistics 59

Statistics Machine Learning Testing Modeling 59

Domino Data Lab

AUGUST 1, 2021

In this article we cover explainability for black-box models and show how to use different methods from the Skater framework to provide insights into the inner workings of a simple credit scoring neural network model. The interest in interpretation of machine learning has been rapidly accelerating in the last decade.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

Domino Data Lab

JULY 9, 2019

Assessing whether a business stakeholder is trying to solve for a problem that is descriptive, predictive, or prescriptive and then re-framing the problem as supervised learning, unsupervised learning, or reinforcement learning, respectively. One of the ways I frame that is, “Are you looking to build a predictive model?

Data Science 112

Data Science Machine Learning Advertising Modeling 112

Occam's Razor

NOVEMBER 18, 2014

Short story #2: Predictive Modeling, Quantifying Cost of Inaction. You get a confusing little thing, but the visualization is interactive. The Treemap, Sunburst and Packedcircle demonstrate three possible paths you can take to go from a table to something much more understandable and much more interactive.

Visualization 143

Visualization Slice and Dice Predictive Modeling Metrics 143

datapine

JANUARY 31, 2022

Everything is being tested, and then the campaigns that succeed get more money put into them, while the others aren’t repeated. This methodology of “test, look at the data, adjust” is at the heart and soul of business intelligence. Your Chance: Want to try a professional BI analytics software?

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

Smarten

JULY 13, 2023

When an organization implements a Citizen Data Scientist initiative, it can leverage Assisted Predictive Modeling and provide advantages to the business users.’ You can explore more business use cases for a variety of business functions and industries here: Predictive Analytics Use Cases For Citizen Data Scientists.

Predictive Modeling 52

Predictive Modeling Predictive Analytics Cost-Benefit Advertising 52

Smarten

JULY 26, 2022

“Users can analyze and interact with data with full visibility of dashboards, reports and other BI objects.” The Smarten Augmented Analytics and BI platform allows business users to leverage deep dive analysis using highly interactive dashboards, reports and NLP search on a mobile device.

Key Performance Indicator 74

Key Performance Indicator Analytics Business Intelligence Dashboards 74

Cloudera

JANUARY 25, 2022

Instead of starting from scratch, Applied ML Prototypes (AMPs ) provides pre-built templates of many commonly used machine learning techniques such as time series forecasting, churn modeling, and anomaly detection. This blueprint the AMP provides can be used to modify any aspect of the project including the model. Invoking the Model

Visualization 91

Visualization Machine Learning Predictive Analytics Data-driven 91

datapine

NOVEMBER 27, 2019

Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. However, businesses today want to go further and predictive analytics is another trend to be closely monitored. Another increasing factor in the future of business intelligence is testing AI in a duel.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Smarten

JUNE 25, 2018

Flexible self-serve business intelligence and analytical tools will ensure data democratization among business users, and provide a comprehensive toolset to be used for planning methods and to test theories and clearly illustrate results by type, time period or other variables.

Statistics 40

Statistics Enterprise Measurement Business Intelligence 40

O'Reilly on Data

MARCH 24, 2020

In a world focused on buzzword-driven models and algorithms, you’d be forgiven for forgetting about the unreasonable importance of data preparation and quality: your models are only as good as the data you feed them. The model and the data specification become more important than the code. Let’s get everybody to do X.

Machine Learning 352

Machine Learning Statistics Data Quality Modeling 352

FineReport

MARCH 31, 2024

Through meticulous testing and research, we’ve curated a list of the ten best BI tools, ensuring accessibility and efficacy for businesses of all sizes. Recognized for its versatility, Power BI excels in data transformation and visualization, incorporating advanced predictive modeling and AI-driven features.

Dashboards 52

Dashboards Visualization Data mining Data-driven 52

Depict Data Studio

SEPTEMBER 17, 2019

You’ll also learn about 508 compliance, like how to test your visuals for sufficient foreground/background contrast, colorblindness legibility, and grayscale legibility using accessibility checkers. . David focuses especially on helping researchers embrace the power of the internet to communicate with online, interactive reporting.

Visualization 40

Visualization Consulting Dashboards Reporting 40

Smarten

DECEMBER 3, 2023

It also augments the expert and citizen data scientists by automating many aspects of data science, machine learning, and AI model development, management and deployment.’ ‘You As Springboard notes, ‘Augmented Analytics is an example of human machine interaction in the data science field.’

Key Performance Indicator 52

Key Performance Indicator Analytics IT Predictive Analytics 52

Smarten

OCTOBER 31, 2022

What-If Analysis to test pricing, budget and cost information. GeoMap support with interactive maps. Deep-Dive Analytics. Social BI tools for data sharing. Graphical Analysis and Cross-Tab Analytics for Intuitive reporting. Out-of-the-Box Mobile BI tools for access from anywhere. Personalized alerts.

Key Performance Indicator 67

Key Performance Indicator Analytics Cost-Benefit Predictive Modeling 67

Jet Global

MAY 1, 2023

As rich, data-driven user experiences are increasingly intertwined with our daily lives, end users are demanding new standards for how they interact with their business data. Embedded Analytics Drive Successful Consumer Applications Consumer web applications have transformed how people use and interact with data.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

Jet Global

SEPTEMBER 1, 2023

Data-Driven Decision Making: Embedded predictive analytics empowers the development team to make informed decisions based on data insights. By integrating predictive models directly into the application, developers can provide real-time recommendations, forecasts, or insights to end-users.

Predictive Analytics 52

Predictive Analytics Risk Analytics Software 52