Rocket-Powered Data Science

DECEMBER 16, 2018

So, you start by assuming a value for k and making random assumptions about the cluster means, and then iterate until you find the optimal set of clusters, based upon some evaluation metric. The above example (clustering) is taken from unsupervised machine learning (where there are no labels on the training data). What data do we have?

Machine Learning 203

Machine Learning Metrics Optimization Data Science 203

Smart Data Collective

JUNE 14, 2022

You can use data mining tools to evaluate feedback from customer surveys and other resources that will help you get a better understanding of their expectations. You can also use your own data analytics dashboards to see what customers are telling you. Use Data Mining to Hone Your Content Creation Skills.

Big Data 122

Big Data Data mining Metrics Sales 122

IBM Big Data Hub

JANUARY 10, 2023

Change programs can spend many weeks conducting interviews and workshops to identify ‘As Is’ pictures. However, we often find a disconnect between what users say is happening, and what data shows is actually happening. Process mining tools automate and generate dashboards which illustrate an ‘at a glance’ view of adoption rates.

Management 52

Management Data-driven Data mining Business Objectives 52

Domino Data Lab

AUGUST 1, 2021

Because of its architecture, intrinsically explainable ANNs can be optimised not just on its prediction performance, but also on its explainability metric. Instead, you should focus on how techniques like PDPs and LIME can be used to gain insights into the model’s inner workings and how you can add those to your data science toolbox.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139