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Description

Apache Mahout is an advanced and adaptable machine learning library that excels in processing distributed datasets efficiently. It encompasses a wide array of algorithms suitable for tasks such as classification, clustering, recommendation, and pattern mining. By integrating seamlessly with the Apache Hadoop ecosystem, Mahout utilizes MapReduce and Spark to facilitate the handling of extensive datasets. This library functions as a distributed linear algebra framework, along with a mathematically expressive Scala domain-specific language, which empowers mathematicians, statisticians, and data scientists to swiftly develop their own algorithms. While Apache Spark is the preferred built-in distributed backend, Mahout also allows for integration with other distributed systems. Matrix computations play a crucial role across numerous scientific and engineering disciplines, especially in machine learning, computer vision, and data analysis. Thus, Apache Mahout is specifically engineered to support large-scale data processing by harnessing the capabilities of both Hadoop and Spark, making it an essential tool for modern data-driven applications.

Description

Daft is an advanced framework designed for ETL, analytics, and machine learning/artificial intelligence at scale, providing an intuitive Python dataframe API that surpasses Spark in both performance and user-friendliness. It integrates seamlessly with your ML/AI infrastructure through efficient zero-copy connections to essential Python libraries like Pytorch and Ray, and it enables the allocation of GPUs for model execution. Operating on a lightweight multithreaded backend, Daft starts by running locally, but when the capabilities of your machine are exceeded, it effortlessly transitions to an out-of-core setup on a distributed cluster. Additionally, Daft supports User-Defined Functions (UDFs) in columns, enabling the execution of intricate expressions and operations on Python objects with the necessary flexibility for advanced ML/AI tasks. Its ability to scale and adapt makes it a versatile choice for data processing and analysis in various environments.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Apache Spark Yes 
Amazon Web Services (AWS) No 
Apache Arrow No 
Apache Iceberg No 
Databricks No 
Delta Lake No 
Google Cloud Platform No 
Hadoop Yes 
JSON No 
Microsoft Azure No 
PyTorch No 
Python No 
Rust No 
Unity Catalog No 
pandas No 

Integrations

Apache Spark Yes 
Amazon Web Services (AWS) Yes 
Apache Arrow Yes 
Apache Iceberg Yes 
Databricks Yes 
Delta Lake Yes 
Google Cloud Platform Yes 
Hadoop No 
JSON Yes 
Microsoft Azure Yes 
PyTorch Yes 
Python Yes 
Rust Yes 
Unity Catalog Yes 
pandas Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Apache Software Foundation

Country

United States

Website

mahout.apache.org

Vendor Details

Company Name

Daft

Country

United States

Website

www.getdaft.io

Product Features

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

Product Features

Data Science

Access Control No 
Advanced Modeling No 
Audit Logs No 
Data Discovery No 
Data Ingestion No 
Data Preparation No 
Data Visualization No 
Model Deployment No 
Reports No 

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