ODSC - Open Data Science

JANUARY 5, 2024

Scikit-learn A machine learning powerhouse, Scikit-learn provides a vast collection of algorithms and tools, making it a go-to library for many data scientists. Interested in attending an ODSC event? Learn more about our upcoming events here. Subscribe to our weekly newsletter here and receive the latest news every Thursday.

Python 52

Python K-nearest Neighbors Data Science Data Visualization 52

Snorkel AI

APRIL 11, 2023

Cody Coleman, CEO and co-founder of Coactive AI gave a presentation entitled “Data Selection for Data-Centric AI: Quality over Quantity” at Snorkel AI’s Future of Data-Centric AI Event in August 2022. So have you tried other clustering approaches other than K-means, and how does that impact this entire process? AB : Got it. Thank you.

K-nearest Neighbors 52

K-nearest Neighbors Clustering Deep Learning Deep Learning 52

Snorkel AI

APRIL 11, 2023

Cody Coleman, CEO and co-founder of Coactive AI gave a presentation entitled “Data Selection for Data-Centric AI: Quality over Quantity” at Snorkel AI’s Future of Data-Centric AI Event in August 2022. So have you tried other clustering approaches other than K-means, and how does that impact this entire process? AB : Got it. Thank you.

K-nearest Neighbors 52

K-nearest Neighbors Clustering Deep Learning Deep Learning 52

Snorkel AI

APRIL 11, 2023

Cody Coleman, CEO and co-founder of Coactive AI gave a presentation entitled “Data Selection for Data-Centric AI: Quality over Quantity” at Snorkel AI’s Future of Data-Centric AI Event in August 2022. So have you tried other clustering approaches other than K-means, and how does that impact this entire process? AB : Got it. Thank you.

K-nearest Neighbors 52

K-nearest Neighbors Clustering Deep Learning Deep Learning 52

Pickl AI

SEPTEMBER 3, 2023

Observations that deviate from the majority of the data are known as anomalies and might take the shape of occurrences, trends, or events that differ from customary or expected behaviour. Finding anomalous occurrences that might point to intriguing or potentially significant events is the aim of anomaly detection.

Machine Learning 52

Machine Learning Machine Learning K-nearest Neighbors Algorithm 52

Heartbeat

SEPTEMBER 22, 2023

Introduction In the world of machine learning, where algorithms learn from data to make predictions, it’s important to get the best out of our models. Steps to Perform Hyperparameter Tuning Hyperparameter Tuning process (Image by author) Select Hyperparameters to Tune: Different algorithms have different hyperparameters.

Machine Learning 64

Machine Learning Machine Learning ML ML 64

Mlearning.ai

MARCH 28, 2023

Class imbalance can occur in various real-world scenarios such as fraud detection, medical diagnosis, and rare event prediction. In these cases, the rare events or positive instances are of great interest, but they are often overshadowed by the abundance of negative instances. Where does it occur?

Machine Learning 52

Machine Learning Machine Learning K-nearest Neighbors Python 52

PyImageSearch

SEPTEMBER 16, 2024

Home Table of Contents Credit Card Fraud Detection Using Spectral Clustering Understanding Anomaly Detection: Concepts, Types and Algorithms What Is Anomaly Detection? Jump Right To The Downloads Section Understanding Anomaly Detection: Concepts, Types, and Algorithms What Is Anomaly Detection? Looking for the source code to this post?

Clustering 56

Clustering Algorithm Machine Learning Machine Learning 56

Pickl AI

SEPTEMBER 12, 2024

A Algorithm: A set of rules or instructions for solving a problem or performing a task, often used in data processing and analysis. Decision Trees: A supervised learning algorithm that creates a tree-like model of decisions and their possible consequences, used for both classification and regression tasks.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52

Snorkel AI

APRIL 28, 2023

He presented “Building Machine Learning Systems for the Era of Data-Centric AI” at Snorkel AI’s The Future of Data-Centric AI event in 2022. Often, it requires you to co-design the algorithm and also the system set. If they’re necessary, how can we create a new algorithm to accommodate it?

ML 52

ML ML Machine Learning Machine Learning 52

Snorkel AI

APRIL 28, 2023

He presented “Building Machine Learning Systems for the Era of Data-Centric AI” at Snorkel AI’s The Future of Data-Centric AI event in 2022. Often, it requires you to co-design the algorithm and also the system set. If they’re necessary, how can we create a new algorithm to accommodate it?

ML 52

ML ML Machine Learning Machine Learning 52

Mlearning.ai

MAY 23, 2023

An interdisciplinary field that constitutes various scientific processes, algorithms, tools, and machine learning techniques working to help find common patterns and gather sensible insights from the given raw input data using statistical and mathematical analysis is called Data Science. What is Data Science? Let us see some examples.

Data Science 52

Data Science Decision Trees Machine Learning Machine Learning 52

DagsHub

DECEMBER 23, 2024

For instance, given a certain sample if the active learning algorithm is uncertain about the correct response it can send the sample to the human annotator. Key Characteristics Synthetic Data Generation : Query synthesis algorithms actively generate new training examples rather than selecting from an existing pool.

Deep Learning 52

Deep Learning Deep Learning Supervised Learning Clustering 52

Dataconomy

SEPTEMBER 1, 2023

The time has come for us to treat ML and AI algorithms as more than simple trends. Hybrid machine learning techniques can help with effective heart disease prediction by combining the strengths of different machine learning algorithms and utilizing them in a way that maximizes their predictive power.

Decision Trees 195

Decision Trees Machine Learning Machine Learning Support Vector Machines 195

Google Research AI blog

NOVEMBER 28, 2022

NeurIPS 2022 will be held as a hybrid event, in person in New Orleans, LA with some virtual attendance options, and includes invited talks, demonstrations and presentations of some of the latest in machine learning research.

Machine Learning 52

Machine Learning Machine Learning Algorithm Clustering 52

Dataconomy

FEBRUARY 26, 2025

It bridges the gap between mere correlation and genuine insight, enabling organizations to make informed decisions based on the root causes of events. Step-by-step process Collect observational data: Gather extensive datasets that track various events over time to inform causal relationships.

K-nearest Neighbors 91

K-nearest Neighbors AI AI Artificial Intelligence 91