IBM Big Data Hub

DECEMBER 19, 2023

For example, higher than average traffic on a website or application for a particular period can signal a cybersecurity threat, in which case you’d want a system that could automatically trigger fraud detection alerts. A machine learning model trained with labeled data will be able to detect outliers based on the examples it is given.

Machine Learning 72

Machine Learning Optimization Unstructured Data Sales 72

Sisense

APRIL 10, 2020

Text data is proliferating at a staggering rate, and only advanced coding languages like Python and R will be able to pull insights out of these datasets at scale. R or Python?”. People looking into data science languages are usually confused about which language they should learn first: R or Python. Python: Versatile workhorse.

Deep Learning 98

Deep Learning Data Science Machine Learning Visualization 98

IBM Big Data Hub

JULY 6, 2023

For example, is the problem related to declining revenue or production bottlenecks? 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

Domino Data Lab

DECEMBER 2, 2020

In this blog post, I will cover a family of techniques known as density-based clustering. Let’s consider an example to make this idea more concrete. Cluster Analysis is an important problem in data analysis. There are many families of data clustering algorithms, and you may be familiar with the most popular one: k-means. Preliminary:

Metrics 116

Metrics KDD Testing Machine Learning 116

Domino Data Lab

JANUARY 14, 2019

This blog post provides insights on how to use the SHAP and LIME Python libraries in practice and how to interpret their output, helping readers prepare to produce model explanations in their own work. In Part 2 we explore these libraries in more detail by applying them to a variety of Python models. Introduction.

Testing 89

Testing Modeling Deep Learning Data Science 89

Domino Data Lab

AUGUST 26, 2019

This article provides an excerpt of “Tuning Hyperparameters and Pipelines” from the book, Machine Learning with Python for Everyone by Mark E. For example, having regularized hyperparameters in place provides the ability control the flexibility of the model. Introduction. Chapter Introduction: Tuning Hyperparameters and Pipelines.

Testing 79

Testing Modeling Machine Learning Metrics 79