datapine

AUGUST 14, 2019

Companies surely need data scientists to help them empower their analytics processes, build a numbers-based strategy that will boost their bottom line, and ensure that enormous amounts of data are translated into actionable insights. But being an inquisitive Sherlock Holmes of data is no easy task. Source: RStudio.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

IBM Big Data Hub

AUGUST 28, 2023

With nearly 5 billion users worldwide—more than 60% of the global population —social media platforms have become a vast source of data that businesses can leverage for improved customer satisfaction, better marketing strategies and faster overall business growth.

Data mining 56

Data mining Machine Learning Deep Learning Marketing 56

IBM Big Data Hub

MAY 17, 2024

Poorly run implementations of traditional or generative AI technology in commerce—such as deploying deep learning models trained on inadequate or inappropriate data—lead to bad experiences that alienate both consumers and businesses.  The applications of AI in commerce are vast and varied.

B2B 69

B2B Interactive Optimization Forecasting 69

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. After cleaning, the data is now ready for processing.

Data Science 110

Data Science Statistics Recreation/Entertainment Predictive Analytics 110

IBM Big Data Hub

DECEMBER 20, 2023

Machine learning (ML) technologies can drive decision-making in virtually all industries, from healthcare to human resources to finance and in myriad use cases, like computer vision , large language models (LLMs), speech recognition, self-driving cars and more. What is machine learning?

Machine Learning 79

Machine Learning Modeling Deep Learning Predictive Modeling 79

IBM Big Data Hub

FEBRUARY 14, 2024

Using machine learning (ML), AI can understand what customers are saying as well as their tone—and can direct them to customer service agents when needed. AI platforms can use machine learning and deep learning to spot suspicious or anomalous transactions.

Cost-Benefit 86

Cost-Benefit Insurance Unstructured Data Machine Learning 86

Domino Data Lab

APRIL 21, 2021

In this article, we’ll discuss the challenge organizations face around fraud detection, how machine learning can be used to identify and spot anomalies that the human eye might not catch. deep learning) there is no guaranteed explainability. It can be implemented as either unsupervised (e.g.

Statistics 69

Statistics Machine Learning Modeling Metrics 69

Domino Data Lab

JULY 9, 2019

Wiggins advocated that data scientists find problems that impact the business; re-frame the problem as a machine learning (ML) task; execute on the ML task; and communicate the results back to the business in an impactful way. I still believe that data science is the craft of trying to apply machine learning to some real world problem.

Data Science 112

Data Science Machine Learning Advertising Modeling 112

Alation

APRIL 14, 2022

They strove to ramp up skills in all manner of predictive modeling, machine learning, AI, or even deep learning. According to Strategies in IT Governance , “[Data] governance is the system by which entities are directed and controlled. Data Governance and Data Security.

Metadata 59

Metadata Data Governance Modeling Data-driven 59