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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

Cleanlab Studio offers a comprehensive solution for managing data quality and executing data-centric AI processes within a unified framework designed for both analytics and machine learning endeavors. Its automated pipeline simplifies the machine learning workflow by handling essential tasks such as data preprocessing, fine-tuning foundation models, optimizing hyperparameters, and selecting the best models for your needs. Utilizing machine learning models, it identifies data-related problems, allowing you to retrain on your refined dataset with a single click. You can view a complete heatmap that illustrates recommended corrections for every class in your dataset. All this valuable information is accessible for free as soon as you upload your data. Additionally, Cleanlab Studio comes equipped with a variety of demo datasets and projects, enabling you to explore these examples in your account right after logging in. Moreover, this user-friendly platform makes it easy for anyone to enhance their data management skills and improve their machine learning outcomes.

Description

MLBox is an advanced Python library designed for Automated Machine Learning. This library offers a variety of features, including rapid data reading, efficient distributed preprocessing, comprehensive data cleaning, robust feature selection, and effective leak detection. It excels in hyper-parameter optimization within high-dimensional spaces and includes cutting-edge predictive models for both classification and regression tasks, such as Deep Learning, Stacking, and LightGBM, along with model interpretation for predictions. The core MLBox package is divided into three sub-packages: preprocessing, optimization, and prediction. Each sub-package serves a specific purpose: the preprocessing module focuses on data reading and preparation, the optimization module tests and fine-tunes various learners, and the prediction module handles target predictions on test datasets, ensuring a streamlined workflow for machine learning practitioners. Overall, MLBox simplifies the machine learning process, making it accessible and efficient for users.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Amazon Redshift
Amazon S3
Databricks Data Intelligence Platform
Dropbox
GitHub
Google Cloud Storage
Hugging Face
JupyterHub
Keras
OpenText Analytics Database (Vertica)
PyTorch
Python
Snowflake
TensorFlow
pandas

Integrations

Amazon Redshift
Amazon S3
Databricks Data Intelligence Platform
Dropbox
GitHub
Google Cloud Storage
Hugging Face
JupyterHub
Keras
OpenText Analytics Database (Vertica)
PyTorch
Python
Snowflake
TensorFlow
pandas

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Cleanlab

Country

United States

Website

cleanlab.ai/

Vendor Details

Company Name

Axel ARONIO DE ROMBLAY

Founded

2017

Website

mlbox.readthedocs.io/en/latest/

Product Features

Data Quality

Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management

Product Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

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