KDnuggets

OCTOBER 10, 2023

So you want to understand your customer base better? Learn how to leverage RFM analysis and K-Means clustering in Python to perform customer segmentation.

Machine Learning 102

Machine Learning 102

Smart Data Collective

NOVEMBER 18, 2020

This new approach has proven to be much more effective, so it is a skill set that people must master to become data scientists. Complex mathematical algorithms are used to segment data and estimate the likelihood of subsequent events. What is Data Science? Where to Use Data Science? Where to Use Data Mining?

Data mining 143

Data mining Data Science Informatics Statistics 143

O'Reilly on Data

MARCH 7, 2019

NLP systems in health care are hard—they require broad general and medical knowledge, must handle a large variety of inputs, and need to understand context. We’re in an exciting decade for natural language processing (NLP). In health care, several applications have already moved from science fiction to reality. are written in English.

Deep Learning 227

Deep Learning Testing Machine Learning Modeling 227

Domino Data Lab

JUNE 8, 2021

We derive a Linear SVM classifier, explain its advantages, and show what the fitting process looks like when solved via CVXOPT – a convex optimisation package for Python. In this blog post we take a deep dive into the internals of Support Vector Machines. 1999) and more. 1999) and more. Derivation of a Linear SVM.

Optimization 76

Optimization Machine Learning Measurement Data Science 76

Domino Data Lab

APRIL 3, 2019

I introduced these themes in “ Three surveys of AI adoption reveal key advice from more mature practices ” and explored them in even more detail in “ Episode 7 ” of this column. Plus, the more mature machine learning (ML) practices place greater emphasis on these kinds of solutions than the less experienced organizations.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Occam's Razor

OCTOBER 21, 2013

In late 2011, Google announced an effort to make search behavior more secure. Logged-in users were switched to using httpS from http. This encrypted their search queries from any prying eyes, and kept from being passed on to websites the users visits after seeing search results. This can place many of our peer citizens in grave danger.

Optimization 154

Optimization Reporting Experimentation Metrics 154

Sisense

SEPTEMBER 25, 2020

In this article, we will explain how to execute five statistical techniques using Python. As datasets become bigger and more complex, only AI, materialized views, and more sophisticated coding languages will be able to glean insights from them. Statistics and programming go hand in hand. Importance of statistical techniques.

Statistics 98

Statistics Predictive Modeling Modeling Machine Learning 98