Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Land Tender empowers decision-makers at various levels to evaluate and respond to risks affecting communities and ecosystems in almost real-time while identifying opportunities to enhance ecosystem advantages. It leverages reliable data at the tree or household level, all presented through an intuitive management interface that accurately reflects on-ground realities. Users can create and analyze an unlimited number of scenarios, tailoring them according to specific objectives and constraints, and simulating outcomes over time. Plans can be monitored and adjusted based on the results of treatments as well as shifts in conditions or goals. The platform facilitates collaboration and fosters quick consensus by enabling users to share scenarios and visualize both similarities and differences effectively. Land Tender offers unmatched transparency regarding the data, modeling, and scientific consensus that inform the best approaches to achieving planning goals. Additionally, it comes with an extensive user manual that includes detailed documentation on strategic resource areas, hazard modeling, and references to the foundational scientific literature. This comprehensive support ensures users have all the tools they need to make informed decisions that benefit both communities and ecosystems.
Description
ML.NET is a versatile, open-source machine learning framework that is free to use and compatible across platforms, enabling .NET developers to create tailored machine learning models using C# or F# while remaining within the .NET environment. This framework encompasses a wide range of machine learning tasks such as classification, regression, clustering, anomaly detection, and recommendation systems. Additionally, ML.NET seamlessly integrates with other renowned machine learning frameworks like TensorFlow and ONNX, which broadens the possibilities for tasks like image classification and object detection. It comes equipped with user-friendly tools such as Model Builder and the ML.NET CLI, leveraging Automated Machine Learning (AutoML) to streamline the process of developing, training, and deploying effective models. These innovative tools automatically analyze various algorithms and parameters to identify the most efficient model for specific use cases. Moreover, ML.NET empowers developers to harness the power of machine learning without requiring extensive expertise in the field.
API Access
Has API
API Access
Has API
Integrations
.NET
Bing
C#
F#
Google Cloud AutoML
Microsoft Defender Antivirus
Microsoft Outlook
Microsoft Power BI
ONNX
TensorFlow
Integrations
.NET
Bing
C#
F#
Google Cloud AutoML
Microsoft Defender Antivirus
Microsoft Outlook
Microsoft Power BI
ONNX
TensorFlow
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
Free
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
Vibrant Planet
Founded
2004
Country
United States
Website
www.vibrantplanet.net/landtender
Vendor Details
Company Name
Microsoft
Founded
1975
Country
United States
Website
dotnet.microsoft.com/en-us/apps/ai/ml-dotnet
Product Features
Forestry
Barcoding / RFID
Contract Management
Cost Accounting
Customer Management
Financial Management
Harvest Management
Order Processing
Pricing Management
Production Tracking
Supplier Management
Transportation Management
Product Features
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization