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Compare Posit and TensorFlow 
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At a Glance
Market Segments
Enterprise (48.6% of reviews)
Small-Business (50.8% of reviews)
Entry-Level Pricing
No pricing available
No pricing available
Posit
Star Rating
(562)4.5 out of 5
Market Segments
Enterprise (48.6% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about PositTensorFlow
Star Rating
(135)4.5 out of 5
Market Segments
Small-Business (50.8% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about TensorFlowSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that Posit excels in data ingestion and wrangling with a score of 9.1, while TensorFlow, with a score of 8.6, is noted to have a more complex setup process for data preparation. Reviewers mention that Posit's user-friendly interface simplifies the data wrangling process significantly.
- Reviewers mention that TensorFlow shines in machine learning capabilities, particularly in artificial neural networks, where it scored 9.3 compared to Posit's 7.6. Users on G2 highlight TensorFlow's extensive library of pre-built algorithms as a major advantage for deep learning projects.
- Users say that Posit offers a better ease of use with a score of 8.3, while TensorFlow's score of 7.6 indicates a steeper learning curve. Reviewers mention that Posit's intuitive design makes it more accessible for beginners in data science.
- G2 users report that TensorFlow has superior support for natural language processing, scoring 9.0 compared to Posit's 8.5. Users highlight TensorFlow's robust features for text analysis and generation as a key differentiator for NLP tasks.
- Reviewers mention that Posit provides a more collaborative environment with a collaboration score of 8.1, while TensorFlow's score of 7.6 suggests it may lack some collaborative features. Users appreciate Posit's focus on teamwork and sharing insights easily among users.
- Users on G2 report that TensorFlow's scalability is impressive, with a score of 9.1, compared to Posit's 8.6. Reviewers mention that TensorFlow's architecture is designed to handle large datasets and complex models efficiently, making it a preferred choice for enterprise-level applications.
Pricing
Entry-Level Pricing
Posit
No pricing availableTensorFlow
No pricing availableFree Trial
Posit
Free Trial is available
TensorFlow
No trial information availableRatings
Meets Requirements
9.1
496
9.2
118
Ease of Use
8.3
496
8.0
121
Ease of Setup
8.8
106
8.3
99
Ease of Admin
8.3
90
7.9
39
Quality of Support
8.1
403
8.7
105
Has the product been a good partner in doing business?
8.5
81
8.3
36
Product Direction (% positive)
8.5
488
9.3
115
Features by Category
Administration
8.7
76
Not enough data
9.2
82
Not enough data
8.2
76
Not enough data
Capabilities
9.0
89
Not enough data
8.9
67
Not enough data
8.9
55
Not enough data
8.8
59
Not enough data
Methodology
9.1
77
Not enough data
9.5
85
Not enough data
9.3
82
Not enough data
Generative AI
Not enough data
Not enough data
Not enough data
Not enough data
System
9.1
25
8.6
70
Model Development
8.8
19
8.9
96
7.8
21
7.2
82
8.3
21
8.8
96
9.0
21
9.2
95
Model Development
9.0
20
9.0
69
Machine/Deep Learning Services
8.6
15
9.1
93
8.5
14
9.0
88
8.7
13
8.8
86
7.6
17
9.4
96
Machine/Deep Learning Services
8.6
17
8.7
64
9.1
18
9.2
68
Deployment
8.4
19
8.5
80
8.9
18
8.7
89
8.7
19
9.0
89
Generative AI
Not enough data
8.0
11
Not enough data
7.7
11
Not enough data
8.0
11
Agentic AI - Data Science and Machine Learning Platforms
Not enough data
7.3
5
Not enough data
7.3
5
Not enough data
8.0
5
Not enough data
8.7
5
Not enough data
8.3
5
Not enough data
7.0
5
Not enough data
7.7
5
Database
9.0
8
Not enough data
9.0
7
Not enough data
8.6
7
Not enough data
Integrations
8.3
5
Not enough data
8.3
6
Not enough data
Platform
7.9
8
Not enough data
8.7
10
Not enough data
8.3
6
Not enough data
Processing
8.3
5
Not enough data
8.1
8
Not enough data
Building Reports
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Platform
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Categories
Categories
Shared Categories
Posit and TensorFlow are categorized as Data Science and Machine Learning Platforms
Unique Categories
Posit is categorized as Statistical Analysis and Big Data Processing and Distribution
TensorFlow has no unique categories
Reviews
Reviewers' Company Size
Posit
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
TensorFlow
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Small-Business
(50 or fewer emp.)
Mid-Market
(51-1000 emp.)
Enterprise
(> 1000 emp.)
Reviewers' Industry
Higher Education
19.1%
Information Technology and Services
12.6%
Research
11.2%
Computer Software
8.7%
Education Management
5.6%
Other
42.8%
Computer Software
27.7%
Information Technology and Services
20.0%
Research
7.7%
Computer & Network Security
4.6%
Higher Education
3.1%
Other
36.9%
Alternatives
Discussions
Can we save our process if we don't save a project?
2 Comments
SL
There are many ways to save results as an R script runs, take a look at the R saveRDS function as one example.
For questions like this about R a great...Read more
What is the best way to run R code within a VBA routine?
1 Comment
PB
I ran into same kind of problems. Then I discovered PowerBI.
With PowerBI, and the help of PowerQuery, I'm getting rid of all VbA engines to process...Read more
Which software is used for R programming?
1 Comment
SH
RStudio is the most popular IDE for running R programs and has a free license. The official R software environment is an open-source free software...Read more
What is TensorFlow and why it is used?
2 Comments
PS
TensorFlow is an open-source library that lets you generate various models AI/ML/DL models.Read more
TensorFlow has no more discussions with answers
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