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Compare Neo4j Graph Data Science and machine-learning in Python 
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At a Glance
Market Segments
Mid-Market (46.7% of reviews)
Enterprise (40.6% of reviews)
Entry-Level Pricing
Starting at $1.00 Per Month
No pricing available
Neo4j Graph Data Science
Star Rating
(16)4.5 out of 5
Market Segments
Mid-Market (46.7% of reviews)
Entry-Level Pricing
Starting at $1.00 Per Month
Browse all 3 pricing plansmachine-learning in Python
Star Rating
(35)4.7 out of 5
Market Segments
Enterprise (40.6% of reviews)
Entry-Level Pricing
No pricing available
Learn more about machine-learning in PythonSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that "machine-learning in Python" excels in "Model Development" with a high score of 9.0 for its "Pre-Built Algorithms," making it easier for developers to implement complex models quickly. In contrast, "Neo4j Graph Data Science" has a slightly lower score of 8.5 in this area, which may limit rapid prototyping for some users.
- Reviewers mention that "machine-learning in Python" offers superior "Data Analysis" capabilities, scoring 9.4, which allows for deeper insights into datasets. On the other hand, "Neo4j Graph Data Science" scores 8.3 in "Data Visualizations," indicating that users may find it less effective for visual representation of data insights.
- G2 users highlight that "machine-learning in Python" provides robust "Integration" options, particularly in "Scripting" with a score of 8.9, which facilitates seamless integration into existing workflows. Conversely, "Neo4j Graph Data Science" has a lower score in this area, suggesting potential challenges in integrating with other tools.
- Users on G2 report that "machine-learning in Python" has a higher "Ease of Setup" score of 8.8, indicating a more user-friendly experience for new users. In contrast, "Neo4j Graph Data Science" scores 7.9, which may pose a steeper learning curve for those unfamiliar with graph databases.
- Reviewers say that "Neo4j Graph Data Science" shines in "Quality of Support," with a score of 8.8, which users appreciate for timely assistance. Meanwhile, "machine-learning in Python" scores 8.4, suggesting that while support is good, it may not be as responsive as that of Neo4j.
- Users report that "machine-learning in Python" has a strong focus on "Scalability," scoring 9.2, which is crucial for handling large datasets effectively. In comparison, "Neo4j Graph Data Science" scores 9.0, indicating it is also scalable but may not match the flexibility offered by Python-based solutions.
Pricing
Entry-Level Pricing
Neo4j Graph Data Science
AuraDS Professional
Starting at $1.00
Per Month
AuraDS Professional is the fastest way to take your graph data science experiments to production with monthly billing.
- 8-96GB (RAM)
- Pay as you go: credit card or Google Cloudbilling
- Automated updates/patches
machine-learning in Python
No pricing availableFree Trial
Neo4j Graph Data Science
No trial information availablemachine-learning in Python
No trial information availableRatings
Meets Requirements
9.0
13
9.0
26
Ease of Use
8.5
13
9.0
29
Ease of Setup
7.9
8
8.8
20
Ease of Admin
8.3
8
9.0
17
Quality of Support
8.8
13
8.4
26
Has the product been a good partner in doing business?
9.4
8
8.9
16
Product Direction (% positive)
9.1
13
10.0
24
Features by Category
System
8.8
10
Not enough data
Model Development
7.9
11
Not enough data
8.1
8
Not enough data
8.5
10
Not enough data
8.5
9
Not enough data
Model Development
8.8
7
Not enough data
Machine/Deep Learning Services
Feature Not Available
Not enough data
8.0
5
Not enough data
Feature Not Available
Not enough data
8.0
5
Not enough data
Machine/Deep Learning Services
Feature Not Available
Not enough data
Not enough data
Not enough data
Deployment
7.9
7
Not enough data
8.8
10
Not enough data
9.2
8
Not enough data
Generative AI
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Agentic AI - Data Science and Machine Learning Platforms
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
Integration - Machine Learning
Not enough data
Not enough data
Learning - Machine Learning
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Statistical Tool
8.9
6
Not enough data
8.6
6
Not enough data
9.2
6
Not enough data
Data Analysis
9.4
6
Not enough data
9.3
5
Not enough data
Decision Making
9.2
6
Not enough data
8.3
5
Not enough data
8.1
6
Not enough data
Not enough data
Not enough data
Generative AI
Not enough data
Not enough data
Not enough data
Not enough data
Categories
Categories
Shared Categories
Neo4j Graph Data Science and machine-learning in Python are categorized as Machine Learning
Unique Categories
Neo4j Graph Data Science is categorized as Data Science and Machine Learning Platforms and Predictive Analytics
machine-learning in Python has no unique categories
Reviews
Reviewers' Company Size
Neo4j Graph Data Science
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
machine-learning in Python
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
Computer Software
26.7%
Marketing and Advertising
13.3%
Information Technology and Services
13.3%
Biotechnology
13.3%
Sports
6.7%
Other
26.7%
Computer Software
25.0%
Information Technology and Services
15.6%
Research
12.5%
Higher Education
6.3%
Telecommunications
3.1%
Other
37.5%
Alternatives
Discussions
Neo4j Graph Data Science has no discussions with answers
Which Python version is best for machine learning?
2 Comments
SM
3.7 or later version is best to use this language.Read more
What is Python with machine learning?
1 Comment
SD
Firstly python is just a way to get machine learning things get done not inter related to machine learning. But using python in machine learning will help...Read more
machine-learning in Python has no more discussions with answers
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