KDnuggets

JULY 4, 2025

By Kanwal Mehreen , KDnuggets Technical Editor & Content Specialist on July 4, 2025 in Machine Learning Image by Author | Canva If you like building machine learning models and experimenting with new stuff, that’s really cool — but to be honest, it only becomes useful to others once you make it available to them.

Machine Learning

Analytics Vidhya

JUNE 11, 2025

However, to develop a good and working ML model, setting up the necessary environments and tools is essential, and sometimes it may create many problems as well. Now, imagine training models like XGBoost directly in your […] The post Browser-Based XGBoost: Train Models Without Jupyter or IDEs appeared first on Analytics Vidhya.

Modeling

KDnuggets

JULY 16, 2025

Transforming this data into meaningful, structured inputs that models can learn from is an essential step — this process is known as feature engineering. Feature engineering can impact model performance, sometimes even more than the choice of algorithm itself. Why is feature engineering important?

Modeling

CIO Business Intelligence

DECEMBER 10, 2024

Large language models (LLMs) just keep getting better. In just about two years since OpenAI jolted the news cycle with the introduction of ChatGPT, weve already seen the launch and subsequent upgrades of dozens of competing models. From Llama3.1 to Gemini to Claude3.5 From Llama3.1 to Gemini to Claude3.5

Modeling

CIO Business Intelligence

OCTOBER 17, 2024

With the prohibitive cost of computing power and other expenses needed to deploy AI models, many businesses not only lack the resources, they also often require help identifying and executing the best use cases. To choose the right AI model, you should first examine how AI can add value to their operations while driving efficiencies.

Modeling

KDnuggets

JUNE 23, 2025

It makes it easier to track experiments, save models, and deploy them. Keeping track of experiments and models can be hard. It helps you track, manage, and deploy models. These tools help develop, deploy, and maintain models. MLflow also manages models after deployment. MLFlow is a tool that makes this easier.

Modeling

CIO Business Intelligence

NOVEMBER 12, 2024

“I would encourage everbody to look at the AI apprenticeship model that is implemented in Singapore because that allows businesses to get to use AI while people in all walks of life can learn about how to do that. So, this idea of AI apprenticeship, the Singaporean model is really, really inspiring.”

Modeling

CIO Business Intelligence

JULY 24, 2025

Microsoft Fabric users will soon face more work to set up analytics workflows for new datasets, as Microsoft is retiring a feature that automatically creates semantic models on enterprise data. Semantic models are structured representations of data that that add meaning and context to the raw information held in Fabric.

Modeling

CIO Business Intelligence

JUNE 13, 2025

Queue Hub, begun in earnest in July 2023, was created using machine learning (ML) algorithms, open-source object detection algorithms, and custom AI models. We are training the models for seasonal, hourly, and event-based patterns, holiday surges, and weather disruptions,” the CIDO says. “It It’s a living system. It’s very fluid.

Modeling

Analytics Vidhya

NOVEMBER 18, 2024

In this tutorial, you will learn how to construct iterate update and train a CNN model using JAX, Flax, and Optax on the MNIST dataset.

Testing

CIO Business Intelligence

DECEMBER 19, 2024

So far, no agreement exists on how pricing models will ultimately shake out, but CIOs need to be aware that certain pricing models will be better suited to their specific use cases. Lots of pricing models to consider The per-conversation model is just one of several pricing ideas.

Cost-Benefit

Smart Data Collective

JUNE 16, 2025

Reading: Thinking Machines At Work: How Generative AI Models Are Redefining Business Intelligence Share Notification Font Resizer Aa Font Resizer Aa Search About Help Privacy Follow US © 2008-23 SmartData Collective. A logistics firm could use these tools to generate alternate transportation models that a human planner might never imagine.

Business Intelligence

Analytics Vidhya

NOVEMBER 26, 2024

Andrew Ng recently released AISuite, an open-source Python package designed to streamline the use of large language models (LLMs) across multiple providers. This innovative tool simplifies the complexities of working with diverse LLMs by allowing seamless switching between models with a simple “provider:model” string.

IT

Analytics Vidhya

OCTOBER 17, 2024

However, numerous models have provided solutions with state-of-the-art performance in object detection. Zero-shot object detection with the Grounding DINO base is another efficient model that allows you to scan through out-of-box images.

Modeling

CIO Business Intelligence

DECEMBER 11, 2024

To solve the problem, the company turned to gen AI and decided to use both commercial and open source models. With security, many commercial providers use their customers data to train their models, says Ringdahl. Thats one of the catches of proprietary commercial models, he says. Its possible to opt-out, but there are caveats.

Cost-Benefit

KDnuggets

JUNE 12, 2025

So every operation you perform — filtering, transforming, modeling — uses linear algebra under the hood. Part 3: Calculus When you train a machine learning model, it learns the optimal values for parameters by optimization. These concepts are particularly important for tree-based models and feature engineering.

Data Science

O'Reilly on Data

JANUARY 21, 2025

The Evolution of Expectations For years, the AI world was driven by scaling laws : the empirical observation that larger models and bigger datasets led to proportionally better performance. This fueled a belief that simply making models bigger would solve deeper issues like accuracy, understanding, and reasoning.

Cost-Benefit

DataFloq

JULY 1, 2025

Graph models also make it easier to track updates, ensure compliance, and maintain data integrity across care journeys. These models also identify subtle correlations across cases, improving diagnostic accuracy. For instance, these models can link the patient demographics with drug interactions to flag high-risk cohorts early.

Modeling

Analytics Vidhya

NOVEMBER 21, 2024

Image segmentation is another popular computer vision task that has applications with different models. Its usefulness across different industries and fields has allowed for more research and improvements.

Modeling

CIO Business Intelligence

NOVEMBER 27, 2024

Recent research shows that 67% of enterprises are using generative AI to create new content and data based on learned patterns; 50% are using predictive AI, which employs machine learning (ML) algorithms to forecast future events; and 45% are using deep learning, a subset of ML that powers both generative and predictive models.

Data Architecture

CIO Business Intelligence

NOVEMBER 27, 2024

Data quality for AI needs to cover bias detection, infringement prevention, skew detection in data for model features, and noise detection. Not all columns are equal, so you need to prioritize cleaning data features that matter to your model, and your business outcomes. asks Friedman.

Enterprise

DataKitchen

JUNE 18, 2025

A dashboard shows anomalous metrics, a machine learning model starts producing bizarre predictions, or stakeholders complain about inconsistent reports. Machine learning models retrain on outdated features. When Timing Goes Wrong: How Latency Issues Cascade Into Data Quality Nightmares As data engineers, we’ve all been there.

Data Quality

CIO Business Intelligence

OCTOBER 28, 2024

Whisper is not the only AI model that generates such errors. In a separate study, researchers found that AI models used to help programmers were also prone to hallucinations. This phenomenon, known as hallucination, has been documented across various AI models. With over 4.2

Risk

O'Reilly on Data

DECEMBER 10, 2024

Alibabas latest model, QwQ-32B-Preview , has gained some impressive reviews for its reasoning abilities. I also tried a few competing models: GPT-4 o1 and Gemma-2-27B. GPT-4 o1 was the first model to claim that it had been trained specifically for reasoning. How do you test a reasoning model? What else can we learn?

Testing

Analytics Vidhya

NOVEMBER 20, 2024

It is crucial to probability theory and a foundational element for more intricate statistical models, ranging from machine learning algorithms to customer behaviour prediction. A key idea in data science and statistics is the Bernoulli distribution, named for the Swiss mathematician Jacob Bernoulli.

Statistics

David Menninger's Analyst Perspectives

JANUARY 15, 2025

ISG Research asserts that by 2027, one-third of enterprises will incorporate comprehensive external measures to enable ML to support AI and predictive analytics and achieve more consistently performative planning models. It can enhance the breadth of analytics available to improve situational awareness and decision-making.

Predictive Modeling

DataFloq

JULY 25, 2025

With organizations deploying additional ML models across production environments, complexity at scale is becoming critical. Based on TensorFlow, TFX is purpose-built to enable a machine learning mode l to go from a trained machine learning model to a production-ready model. billion in 2025, representing an increase from USD 2.19

Machine Learning

CIO Business Intelligence

DECEMBER 11, 2024

We are now deciphering rules from patterns in data, embedding business knowledge into ML models, and soon, AI agents will leverage this data to make decisions on behalf of companies. If a model encounters an issue in production, it is better to return an error to customers rather than provide incorrect data.

Management

Analytics Vidhya

JANUARY 7, 2025

Fine-tuning large language models (LLMs) is an essential technique for customizing LLMs for specific needs, such as adopting a particular writing style or focusing on a specific domain. OpenAI and Google AI Studio are two major platforms offering tools for this purpose, each with distinct features and workflows.

Modeling

Analytics Vidhya

JULY 29, 2025

Bad quality of data leads to erroneous models, misleading insights, and costly business decisions. The quality of data used is the cornerstone of any data science project. In this comprehensive guide, we’ll explore the construction of a powerful and concise data cleaning and validation pipeline using Python.

Data Science