TDAN

AUGUST 17, 2021

If you are planning on using predictive algorithms, such as machine learning or data mining, in your business, then you should be aware that the amount of data collected can grow exponentially over time.

Predictive Modeling 115

Predictive Modeling Modeling Data mining Big Data 115

IBM Big Data Hub

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? What is machine learning?

Machine Learning 60

Machine Learning Data Science Statistics Deep Learning 60

Sisense

APRIL 10, 2020

We’ll actually do this later in this article. These support a wide array of uses, such as data analysis, manipulation, visualizations, and machine learning (ML) modeling. Some standard Python libraries are Pandas, Numpy, Scikit-Learn, SciPy, and Matplotlib. Modeling in R and Python. R libraries.

Deep Learning 98

Deep Learning Data Science Machine Learning Visualization 98

Rocket-Powered Data Science

JULY 6, 2021

I provide below my perspective on what was interesting, innovative, and influential in my watch list of the Top 10 data innovation trends during 2020. 1) Automated Narrative Text Generation tools became incredibly good in 2020, being able to create scary good “deep fake” articles.

Data-driven 279

Data-driven Machine Learning IoT Deep Learning 279

datapine

MARCH 25, 2022

There is not a clear line between business intelligence and analytics, but they are extremely connected and interlaced in their approach towards resolving business issues, providing insights on past and present data, and defining future decisions. Your Chance: Want to extract the maximum potential out of your data?

Business Intelligence 264

Business Intelligence Analytics Statistics Dashboards 264

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

datapine

NOVEMBER 27, 2019

DQM consists of acquiring the data, implementing advanced data processes, distributing the data effectively and managing oversight data. We detailed the benefits and costs of good or bad quality data in our previous article on data quality management , where you can read the five important pillars to follow.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361