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Learn about the basics of algorithms - what they are, how they work, and how they're used in software development. This article provides an introduction to this fundamental concept in computer science.
Learn about analytics use cases with Graphext's glossary. Discover how analytics use cases can help you make data-driven decisions and improve your business strategy.
Annoy is an open-source library developed by Spotify for fast approximate nearest neighbor searches in large datasets. It efficiently searches through millions of vectors in high-dimensional data, making it ideal for machine learning and data science tasks. Learn more about Annoy and its applications in recommendation systems, fraud detection, and image/text processing.
Learn about the differences between Approximate Nearest Neighbors (ANN) and k-Nearest Neighbors (KNN) algorithms in data science. Discover how ANN can improve computational efficiency, and how KNN can provide more accurate results. Find out which algorithm is best suited for your specific application.
Learn about Arima, a statistical technique for time series analysis used in data science. Discover how it can be applied to business and its uses in forecasting sales, website traffic, and financial metrics. Find out more at Graphext's glossary.
Arrow is a high-performance columnar memory format that speeds up data processing and communication between systems. Learn how Arrow can help businesses optimize data processing and improve data quality.
Learn about attrition analysis, an advanced analytics use case, with Graphext. Understand how to analyze and interpret data to reduce customer or employee attrition. Explore more on our website.
Learn about the statistical concept of average and how it can provide valuable insights into datasets. Discover how to calculate the average using Graphext's built-in aggregation function.
BERT (Bidirectional Encoder Representations from Transformers) is a pre-trained deep learning model for natural language processing tasks, including text classification and named entity recognition. Developed by Google, it has achieved state-of-the-art results in many NLP benchmarks. Businesses can use BERT to extract insights from large volumes of text data, such as sentiment analysis, customer support, and chatbots. Learn more about BERT and its applications on our page.
Learn about backwards feature elimination, a technique used to reduce the number of irrelevant features in data and improve the accuracy and efficiency of predictive models. Recursive Feature Elimination (RFE) and Sequential Feature Selection (SFS) are two effective algorithms for backwards feature elimination. Discover how to apply this technique in business and improve decision-making based on data analysis. Check out the resources provided to learn more.
Learn about the Bayesian Algorithm, a statistical approach widely used in data science, machine learning, and artificial intelligence. Discover how it can be applied to business, including customer segmentation, risk analysis, and fraud detection. Read more at Graphext's glossary.
BigQuery is a fully managed enterprise data warehouse that allows you to manage and analyze your data with built-in features like machine learning, geospatial analytics, and business intelligence. Learn about its scalability, integrations, and how it can be applied to business in this comprehensive guide.
Meta Description: Discover the best books for learning with our comprehensive guide. From classic literature to modern how-to guides, we have everything you need to expand your knowledge.
Learn about box plots, a type of chart used to display the distribution of a dataset. This article covers their key features, how to use them to compare distributions and identify outliers, and their applications in business.
Discover the basics of business data roles with our comprehensive glossary. Learn about the different roles and responsibilities involved in managing business data. This article was created by Victoriano Izquierdo and is currently active on Webflow.
CDC (Change Data Capture) is a data engineering concept used to track and record changes made to data in a database. This glossary entry provides information on CDC, including its definition, relevance for using Graphext, and also known as.
CLIP is a software library for natural language processing and computer vision tasks. Developed by OpenAI, it uses contrastive learning to create a joint embedding space for text and images, allowing for cross-modal retrieval and transfer learning. Learn more about CLIP on Graphext's glossary of machine learning terms.
Learn about CSV files and their importance in modern data processing and analysis. This article explains what a CSV file is, its key highlights, and how it's used in business. Discover how to work with CSV files and why understanding them is crucial for data scientists and business analysts.
CatBoost is a powerful open-source gradient boosting library for machine learning tasks, particularly suited for handling categorical data. Learn about its key features and how it can be applied in business to improve model accuracy and make data-driven decisions. Check out the official website, documentation, and GitHub repository for more information.
Learn the basics of data visualization with this introduction to charts. Understand the relevance of charts for using Graphext and discover how to create effective visualizations for your data.
Churn Analysis is the process of understanding why customers stop doing business with a company and implementing strategies to retain them. This article provides an overview of the steps involved in churn analysis and offers solutions to common problems businesses may face. By analyzing churn, businesses can improve customer satisfaction and profitability.
