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features
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support

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Description

AutoKeras, an AutoML framework built on Keras, is designed by the DATA Lab at Texas A&M University. Its primary objective is to democratize machine learning, making it accessible to a wider audience. With an exceptionally user-friendly interface, AutoKeras facilitates a variety of tasks, enabling users to engage with machine learning effortlessly. This innovative approach removes many barriers, allowing individuals without extensive technical knowledge to leverage advanced machine learning techniques.

Description

Experience the entire journey of developing machine learning algorithms and forecasting results with just a single click. Not every dataset is inherently suitable for machine learning; leverage the Data Dialog to effortlessly refine your data without the hassle of file manipulation. You can easily distribute your prediction reports among your team or make them publicly accessible, allowing anyone to engage with your model and generate predictions. Integrate dynamic ML predictions directly into your application through our user-friendly low-code API. Assess factors like willingness to pay, evaluate leads, and more, all in real-time. Obviously AI equips you with the latest groundbreaking algorithms while ensuring top-notch performance is maintained. You can now accurately forecast revenue, streamline supply chains, and tailor marketing efforts to individual needs. With just a CSV upload or a quick integration with your preferred data sources, you can select your prediction column from a convenient dropdown menu and watch as we automatically construct the AI for you. Additionally, enjoy beautifully crafted visualizations of predicted outcomes, identify key influencers, and explore "what-if" scenarios to better understand potential futures. This innovative approach transforms the way you interact with data and make predictions.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Airtable No 
Amazon Redshift No 
Chartio No 
Docker Yes 
E2E Cloud Yes 
GitHub Yes 
Google Analytics No 
Google Cloud BigQuery No 
HubSpot CRM No 
HubSpot Customer Platform No 
Kaggle No 
Keras Yes 
Nocode HQ No 
PyCharm Yes 
Python Yes 
Salesforce No 
Shopify No 
Stackreaction No 
Typeform No 
Zapier No 

Integrations

Airtable Yes 
Amazon Redshift Yes 
Chartio Yes 
Docker No 
E2E Cloud No 
GitHub No 
Google Analytics Yes 
Google Cloud BigQuery Yes 
HubSpot CRM Yes 
HubSpot Customer Platform Yes 
Kaggle Yes 
Keras No 
Nocode HQ Yes 
PyCharm No 
Python No 
Salesforce Yes 
Shopify Yes 
Stackreaction Yes 
Typeform Yes 
Zapier Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

$75 per month
Free Trial No 
Free Version No 

Deployment

Web-Based No 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
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 Yes 
Live Rep (24/7) Yes 
Online Support Yes 

Types of Training

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

Types of Training

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

Vendor Details

Company Name

AutoKeras

Country

United States

Website

autokeras.com

Vendor Details

Company Name

Obviously AI

Founded

2019

Country

United States

Website

www.obviously.ai/

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

Artificial Intelligence

Chatbot No 
For Healthcare No 
For Sales No 
For eCommerce No 
Image Recognition No 
Machine Learning No 
Multi-Language No 
Natural Language Processing No 
Predictive Analytics No 
Process/Workflow Automation No 
Rules-Based Automation No 
Virtual Personal Assistant (VPA) No 

Big Data

Collaboration No 
Data Blends No 
Data Cleansing No 
Data Mining No 
Data Visualization No 
Data Warehousing No 
High Volume Processing No 
No-Code Sandbox No 
Predictive Analytics No 
Templates No 

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 

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 

No-Code Development

AI-Assisted Development No 
Business Process Automation No 
Collaborative Development No 
Data Aggregation and Publishing No 
Deployment Management No 
Drag & Drop No 
Integrations Management No 
Iteration Management No 
Performance Monitoring No 
Requirements Management No 
Templates No 
Visual Modeling No 
Web / Mobile App Development No 
Workflow Management No 

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