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Compare XGBoost and machine-learning in Python 
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At a Glance
Market Segments
Small-Business (50.0% of reviews)
Enterprise (40.6% of reviews)
Entry-Level Pricing
No pricing available
No pricing available
XGBoost
Star Rating
(13)4.4 out of 5
Market Segments
Small-Business (50.0% of reviews)
Entry-Level Pricing
No pricing available
Learn more about XGBoostmachine-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 XGBoost excels in handling large datasets efficiently, with its gradient boosting framework allowing for faster training times compared to traditional machine-learning methods in Python.
- Reviewers mention that while XGBoost has a steeper learning curve, its performance in predictive accuracy is often superior, particularly in competitions and real-world applications.
- G2 users highlight that machine-learning in Python offers a more user-friendly experience, especially for beginners, due to its extensive libraries like Scikit-learn and TensorFlow, which simplify the implementation of various algorithms.
- Users on G2 report that XGBoost's integration capabilities with other data processing tools are robust, making it a preferred choice for users who require seamless workflows in data science projects.
- Reviewers say that the community support for machine-learning in Python is vast, with numerous tutorials and forums available, which can be a significant advantage for users seeking help and resources.
- Users mention that XGBoost's feature importance capabilities provide actionable insights that help in understanding model predictions, a feature that some users feel is less emphasized in general machine-learning libraries in Python.
Pricing
Entry-Level Pricing
XGBoost
No pricing availablemachine-learning in Python
No pricing availableFree Trial
XGBoost
No trial information availablemachine-learning in Python
No trial information availableRatings
Meets Requirements
9.2
11
9.0
26
Ease of Use
8.9
11
9.0
29
Ease of Setup
8.5
10
8.8
20
Ease of Admin
8.3
9
9.0
17
Quality of Support
7.6
9
8.4
26
Has the product been a good partner in doing business?
8.3
6
8.9
16
Product Direction (% positive)
6.5
10
10.0
24
Features by Category
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
Categories
Categories
Shared Categories
XGBoost and machine-learning in Python are categorized as Machine Learning
Unique Categories
XGBoost has no unique categories
machine-learning in Python has no unique categories
Reviews
Reviewers' Company Size
XGBoost
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
25.0%
Financial Services
16.7%
Research
8.3%
Marketing and Advertising
8.3%
Information Technology and Services
8.3%
Other
33.3%
Computer Software
25.0%
Information Technology and Services
15.6%
Research
12.5%
Higher Education
6.3%
Telecommunications
3.1%
Other
37.5%
Discussions
XGBoost 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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