Data Science 101

OCTOBER 31, 2019

The former is a term used for models where the data has been labeled, whereas, unsupervised learning, on the other hand, refers to unlabeled data. Classification is a form of supervised learning technique where a known structure is generalized for distinguishing instances in new data. Classification. Regression.

Data Mining 77

Data Mining Data Mining Data Mining Data Science 77

Dataconomy

APRIL 4, 2023

Reminder : Training data refers to the data used to train an AI model, and commonly there are three techniques for it: Supervised learning: The AI model learns from labeled data, which means that each data point has a known output or target value. AI models can be trained to recognize patterns and make predictions.

K-nearest Neighbors 91

K-nearest Neighbors Decision Trees AI AI 91

Dataconomy

APRIL 4, 2023

Reminder : Training data refers to the data used to train an AI model, and commonly there are three techniques for it: Supervised learning: The AI model learns from labeled data, which means that each data point has a known output or target value. AI models can be trained to recognize patterns and make predictions.

K-nearest Neighbors 91

K-nearest Neighbors Decision Trees AI AI 91

Pickl AI

APRIL 2, 2024

There are three main types, each serving a distinct purpose: Descriptive Analytics (Business Intelligence): This focuses on understanding what happened. ” Predictive Analytics (Machine Learning): This uses historical data to predict future outcomes. ” or “What are our customer demographics?”

Data Science 52

Data Science Machine Learning Machine Learning Predictive Analytics 52

Dataconomy

MARCH 27, 2023

Some of the ways in which ML can be used in process automation include the following: Predictive analytics:  ML algorithms can be used to predict future outcomes based on historical data, enabling organizations to make better decisions.

ML 70

ML ML Machine Learning Machine Learning 70

Pickl AI

JULY 12, 2024

Jupyter notebooks allow you to create and share live code, equations, visualisations, and narrative text documents. Machine Learning algorithms are trained on large amounts of data, and they can then use that data to make predictions or decisions about new data.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Python Natural Language Processing 52

ODSC - Open Data Science

APRIL 26, 2023

This is seen by NLP models analyzing medical literature and regulatory documents. ClosedLoop gives providers the ability to make accurate, explainable, and actionable predictions about individual health risks based on data fed into the program, the goal of which is to diagnose and treat issues sooner when it would be less costly.

AI 52

AI AI Algorithm Natural Language Processing 52

The MLOps Blog

MARCH 21, 2023

Machine learning platform in healthcare There are mostly three areas of ML opportunities for healthcare, including computer vision, predictive analytics, and natural language processing. You can read this article to learn how to choose a data labeling tool. Let’s look at the healthcare vertical for context.

Machine Learning 69

Machine Learning Machine Learning Data Scientist ML 69