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GoLearn VS XGBoost

Compare GoLearn VS XGBoost and see what are their differences

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Contents:
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  2. » Videos
  3. » Reviews
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GoLearn logo GoLearn

GoLearn is a machine learning library for Go that implements the scikit-learn interface of Fit/Predict.

XGBoost logo XGBoost

XGBoost is an optimized distributed gradient boosting library designed to be highly efficient, flexible and portable.
  • GoLearn Landing page
    Landing page //
    2023-10-07
  • XGBoost Landing page
    Landing page //
    2023-07-30

GoLearn videos

+ Add

GoLearn Pole Dancing iPhone App DayFly Review

More videos:

  • Review - Nikolai Bratkovski of Opencare.com Reviews GoLearn.io & Joshua Lombardo Bottema
  • Review - Ping Hsu From Spotted Properties Reviews GoLearn.io & Joshua Lombardo-Bottema

XGBoost videos

+ Add

XGBoost Part 3: Mathematical Details

More videos:

  • Review - XGBoost A Scalable Tree Boosting System June 02, 2016
  • Review - Free Udemy Course - CatBoost vs XGBoost - Classification and Regression Modeling with Python

Category Popularity

0-100% (relative to GoLearn and XGBoost)

GoLearn

XGBoost

Data Science And Machine Learning
40 40%
Data Science And Machine Learning
60% 60
Data Science Tools
52 52%
Data Science Tools
48% 48
Business & Commerce
0 0%
Business & Commerce
100% 100
Data Dashboard
100 100%
Data Dashboard
0% 0

User comments

Share your experience with using GoLearn and XGBoost. For example, how are they different and which one is better?
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Social recommendations and mentions

XGBoost might be a bit more popular than GoLearn. We know about 1 link to it since March 2021 and only 1 link to GoLearn. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

GoLearn mentions (1)

  • Multi-layer neural network from scratch in Go
    If you're curious about a more robust machine learning library in Go, https://github.com/sjwhitworth/golearn is a quite feature-rich option. Source: over 2 years ago

XGBoost mentions (1)

  • CS Internship Questions
    By the way, most of the time XGBoost works just as well for projects, would not recommend applying deep learning to every single problem you come across, it's something Stanford CS really likes to showcase when it's well known (1) that sometimes "smaller"/less complex models can perform just as well or have their own interpretive advantages and (2) it is well known within ML and DS communities that deep learning... Source: almost 2 years ago

What are some alternatives?

When comparing GoLearn and XGBoost, you can also consider the following products

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

machine-learning in Python - Do you want to do machine learning using Python, but you’re having trouble getting started? In this post, you will complete your first machine learning project using Python.

Open Text Magellan - OpenText Magellan - the power of AI in a pre-wired platform that augments decision making and accelerates your business. Learn more.

Google Cloud TPU - Custom-built for machine learning workloads, Cloud TPUs accelerate training and inference at scale.

Amazon Forecast - Accurate time-series forecasting service, based on the same technology used at Amazon.com. No machine learning experience required.

Kira - Gain visibility into contract repositories, accelerate and improve the accuracy of contract review, mitigate risk of errors, win new business, and improve the value you provide to your clients.

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