Data Science Dojo

AUGUST 11, 2023

The flexibility of Python extends to its ability to integrate with other technologies, enabling data scientists to create end-to-end data pipelines that encompass data ingestion, preprocessing, modeling, and deployment. Decision trees are used to classify data into different categories.

Data Science 195

Data Science Python Data Scientist Decision Trees 195

Iguazio

JUNE 25, 2023

Clustering Metrics Clustering is an unsupervised learning technique where data points are grouped into clusters based on their similarities or proximity. Evaluation metrics include: Silhouette Coefficient - Measures the compactness and separation of clusters.

ML 52

ML ML Clustering Cross Validation 52

ODSC - Open Data Science

JANUARY 7, 2025

Data Engineering Data engineering remains integral to many data science roles, with workflow pipelines being a key focus. Tools like Apache Airflow are widely used for scheduling and monitoring workflows, while Apache Spark dominates big data pipelines due to its speed and scalability.

Data Scientist 40

Data Scientist Data Science Machine Learning Machine Learning 40

DagsHub

DECEMBER 23, 2024

Balanced Dataset Creation Balanced Dataset Creation refers to active learning's ability to select samples that ensure proper representation across different classes and scenarios, especially in cases of imbalanced data distribution. Relies on explicit decision boundaries or feature representations for sample selection.

Deep Learning 52

Deep Learning Deep Learning Supervised Learning Clustering 52

DagsHub

APRIL 21, 2024

It offers implementations of various machine learning algorithms, including linear and logistic regression , decision trees , random forests , support vector machines , clustering algorithms , and more. It is commonly used in MLOps workflows for deploying and managing machine learning models and inference services.

Machine Learning 59

Machine Learning Machine Learning ML ML 59