CIO Business Intelligence

MARCH 5, 2024

CIOs and IT leaders are at the center and must decide what copilots to test, who should receive access, and whether experiments are delivering business value. Today, top AI-assistant capabilities delivering results include generating code, test cases, and documentation. So, what delivers on the productivity promise today?

Cost-Benefit 124

Cost-Benefit Advertising Experimentation Software 124

O'Reilly on Data

JANUARY 17, 2023

Building Models. A common task for a data scientist is to build a predictive model. You’ll try this with a few other algorithms, and their respective tuning parameters–maybe even break out TensorFlow to build a custom neural net along the way–and the winning model will be the one that heads to production.

Machine Learning 325

Machine Learning Predictive Modeling Software Modeling 325

Sisense

SEPTEMBER 25, 2020

No matter your skill, career level, or title, the ability to analyze, organize, and visualize data are vital skills in our world of quickly growing and ever-changing data. Linear regression is a form of supervised learning (or predictive modeling). Y_train and y_test is the target variable of the training and test datasets.

Statistics 98

Statistics Predictive Modeling Modeling Machine Learning 98

Alation

APRIL 14, 2022

Visual Profiling. Automatic sampling to test transformation. They strove to ramp up skills in all manner of predictive modeling, machine learning, AI, or even deep learning. These factors risk data originating in far-flung environments, where the data structures and semantics are not well understood or documented.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

DataRobot Blog

DECEMBER 1, 2022

For example, you could set up a data pipeline that delivers DataRobot predictions to HubSpot to automatically initiate offers within the business rules you set. You could also use the predictions to visualize a BI dashboard or report for your marketing managers to access. Training and Testing Different AI Models.

Machine Learning 52

Machine Learning Marketing Modeling Statistics 52

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. Built-in Code Snippets and Interactive Visualizations to Accelerate Experimentation. There are no black boxes in DataRobot , meaning that there is an explanation for every prediction, as well as every model.

Experimentation 52

Experimentation Machine Learning Data Science Modeling 52

Occam's Razor

NOVEMBER 18, 2014

Like a vast majority on planet Earth, I love data visualizations. A day-to-day manifestation of this love is on my Google+ or Facebook profiles where 75% of my posts are related to my quick analysis and learnings from a visualization. Data visualized is data understood. But for a visual person like me, this is the ah-ha moment.

Visualization 143

Visualization Slice and Dice Predictive Modeling Metrics 143

Domino Data Lab

OCTOBER 23, 2019

You can add a Makefile command test that will run all of your notebooks by issuing. test: py.test --nbval notebooks/*.ipynb. In addition, having a larger set of data such that the model could be split into test versus training data would ensure better accuracy and reduce the chance of overfitting. In Figure 6.8,

Statistics 59

Statistics Machine Learning Testing Modeling 59

Domino Data Lab

AUGUST 20, 2019

The problem is that a new unique identifier of a test example won’t be anywhere in the tree. Feature extraction means moving from low-level features that are unsuitable for learning—practically speaking, we get poor testing results—to higher-level features which are useful for learning. Separate out a hold-out test set.

Testing 68

Testing Modeling Interactive Measurement 68

Domino Data Lab

AUGUST 22, 2019

There are steps you can take to preprocess natural language data such that the modeling you carry out downstream may be more accurate. Common natural language preprocessing options include: Tokenization: This is the splitting of a document (e.g., Execute gutenberg.fileids() to print the names of all 18 documents.)

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

Domino Data Lab

JULY 9, 2019

Diving into examples of building and deploying ML models at The New York Times including the descriptive topic modeling-oriented Readerscope (audience insights engine), a prediction model regarding who was likely to subscribe/cancel their subscription, as well as prescriptive example via recommendations of highly curated editorial content.

Data Science 112

Data Science Machine Learning Advertising Modeling 112

Depict Data Studio

SEPTEMBER 17, 2019

In my sixth year of self-employment, the demand for data visualization skills is stronger than ever. This training program is about classic data visualization principles? advanced techniques like applying data visualization principles to reports, slideshows, infographics, and dashboards. What’s Included. We’ll go broad?

Visualization 40

Visualization Consulting Dashboards Reporting 40

Rocket-Powered Data Science

SEPTEMBER 20, 2021

We would be able to go far beyond searching for correctly spelled column headings in databases or specific keywords in data documentation, to find the data we needed (assuming we even knew the correct labels, metatags, and keywords used by the dataset creators). That’s data democratization. That’s insights democratization.

Data Science 285

Data Science Forecasting Business Intelligence Sales 285

Domino Data Lab

AUGUST 1, 2021

In this article we’ll use Skater , a freely available framework for model interpretation, to illustrate some of the key concepts above. Skater provides a wide range of algorithms that can be used for visual interpretation (e.g. layer-wise relevance propagation), model distillation (e.g. A12 : 0 <= … < 200 DM.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

datapine

NOVEMBER 27, 2019

Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. Companies are no longer wondering if data visualizations improve analyses but what is the best way to tell each data-story. 2) Data Discovery/Visualization. Data exploded and became big.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Jet Global

MAY 1, 2023

Plus, there is an expectation that tools be visually appealing to boot. In the past, data visualizations were a powerful way to differentiate a software application. Their dashboards were visually stunning. Today, free visualizations seem to be everywhere. It’s all about context. End users expect more from analytics too.

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