What is better Wolfram Mathematica or 7Learnings? You have so many Predictive Analysis Software solutions in today’s market that selecting the best product may be frustrating. On our comparison page, you can easily evaluate the functions, pricing terms, available plans, and more details of Wolfram Mathematica and 7Learnings.
You can evaluate their score (9.5 for Wolfram Mathematica vs. 8.7 for 7Learnings) and user satisfaction level (99% for Wolfram Mathematica vs. 95% for 7Learnings). The scores and ratings offer you a solid idea how both these software products perform. Moreover, find out if the application can integrate with the company’s current business apps to promote greater productivity.
Our experts made sure to prepare reviews of all popular Predictive Analysis Software services offered on the market, but among all the ones we reviewed these three caught our special attention: Wolfram Mathematica, Microsoft Azure Machine Learning Studio, Sisense.
Wolfram Mathematica provides a detailed enterprise pricing structure with different pricing groups for home & hobby, students, education, government, and industry. Visit the vendor pricing page to select a plan that meets your specific needs:
Standard Cloud @ $170/month or $1350/year
Full access to Wolfram Knowledgebase and Language
CDF in the Cloud and static deployment interface
15GB cloud storage
300/month Wolfram| API calls
10000/month cloud credits
10 minutes computational limits
2GB session memory limit
1GB file size limit
Free cloud app
Email+ phone support
Standard Desktop @ $2700 or $1350/year (Alternative licensing)
Full access to Wolfram Knowledgebase and Language
Free CDF deployment
8 computational kernels
6000/month Wolfram API calls
Basic access to Wolfram cloud
Email and phone support
complimentary upgrades
Free personal use license
WebMathematica Amateur
Lightweight Grid Manager
Enterprise CDF deployment
2000/month additional Wolfram API calls
Standard Desktop/Cloud @ $2970 or $1485/year (alternative licensing)
Everything in the Standard Cloud and Desktop plans
Wolfram Mathematica integrates with the following applications:
LinkageDesigner
Global Optimization
Lenslab
AceFEM System
Analog Insydes
BEST DB Editor
AceGen
MathOptimizer
Objectica
VisualDSolve
Languages Supported
English
Chinese
German
Hindi
Japanese
Spanish
French
Russian
Italian
Dutch
Portugese
Polish
Turkish
Swedish
Arabic
Prominent Clients
Enova, St. Marche Supermarkets, The Procter & Gamble Company
Available Devices
Windows
Linux
Android
iPhone/iPad
Mac
Web-based
Windows Mobile
Company Size
Small Business
Large Enterprises
Medium Business
Freelancers
Available Support
email
phone
live support
training
tickets
General Info
A modern computational software that handles all facets of technical computing including machine learning, visualizations, data science, geometry, image processing, and neural networks.
7Learnings can seamlessly integrate with various third party platforms, such as:
Google Analytics
Amazon
BigQuery
Snowflake
Azure Blob Storage
Languages Supported
English
Chinese
German
Hindi
Japanese
Spanish
French
Russian
Italian
Dutch
Portugese
Polish
Turkish
Swedish
Arabic
Prominent Clients
WestWing, babymarkt, vitafy
Available Devices
Windows
Linux
Android
iPhone/iPad
Mac
Web-based
Windows Mobile
Company Size
Small Business
Large Enterprises
Medium Business
Freelancers
Available Support
email
phone
live support
training
tickets
General Info
7Learnings provides retailers with advanced price optimization tools. The system accurately predicts price point demand using powerful machine learning models.
The software examined on this page are merely a small part of our entire Predictive Analysis Software category and you should take into account that there may be more reliable solutions out there. If you want to guarantee you make the best possible choice for your team we strongly urge you to compare more products first. You may also want to check out our top 10 Predictive Analysis Software ranking to learn which products are in the current year the highest-rated ones and dominate the market.
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