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Caffe2 VS Scikit-learn

Compare Caffe2 VS Scikit-learn and see what are their differences

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Caffe2 logo Caffe2

A New Lightweight, Modular, and Scalable Deep Learning Framework

Scikit-learn logo Scikit-learn

scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
  • Caffe2 Landing page
    Landing page //
    2021-09-30
  • Scikit-learn Landing page
    Landing page //
    2022-05-06

Caffe2 videos

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Scikit-learn videos

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Learning Scikit-Learn (AI Adventures)

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  • Review - Python Machine Learning Review | Learn python for machine learning. Learn Scikit-learn.

Category Popularity

0-100% (relative to Caffe2 and Scikit-learn)

Caffe2

Scikit-learn

Data Science And Machine Learning
4 4%
Data Science And Machine Learning
96% 96
AI
100 100%
AI
0% 0
Data Science Tools
0 0%
Data Science Tools
100% 100
Business & Commerce
100 100%
Business & Commerce
0% 0

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Caffe2 and Scikit-learn

Caffe2 Reviews

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Scikit-learn Reviews

15 data science tools to consider using in 2021
Scikit-learn is an open source machine learning library for Python that's built on the SciPy and NumPy scientific computing libraries, plus Matplotlib for plotting data. It supports both supervised and unsupervised machine learning and includes numerous algorithms and models, called estimators in scikit-learn parlance. Additionally, it provides functionality for model...
Source: searchbusinessanalytics.techtarget.com

Social recommendations and mentions

Based on our record, Scikit-learn seems to be more popular. It has been mentiond 27 times since March 2021. 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.

Caffe2 mentions (0)

We have not tracked any mentions of Caffe2 yet. Tracking of Caffe2 recommendations started around Mar 2021.

Scikit-learn mentions (27)

  • Link Prediction With node2vec in Physics Collaboration Network
    Firstly, we need a connection to Memgraph so we can get edges, split them into two parts (train set and test set). For edge splitting, we will use scikit-learn. In order to make a connection towards Memgraph, we will use gqlalchemy. - Source: dev.to / 10 months ago
  • WiFilter is a RaspAP install extended with a squidGuard proxy to filter adult content. Great solution for a family, schools and/or public access point
    The ML component is based on scikit-learn which differentiates it from purely list-based filters. It couples this with a full-featured wireless router (RaspAP) in a single device, so it fulfills the needs of a use case not entirely addressed by Pi-hole. Source: 11 months ago
  • PSA: You don't need fancy stuff to do good work.
    Finally, when it comes to building models and making predictions, Python and R have a plethora of options available. Libraries like scikit-learn, statsmodels, and TensorFlowin Python, or caret, randomForest, and xgboostin R, provide powerful machine learning algorithms and statistical models that can be applied to a wide range of problems. What's more, these libraries are open-source and have extensive... Source: 12 months ago
  • Help on using R for Machine Learning?
    Scikit-learn is a machine learning library that comes with a number of pre-built machine learning models, which can then be used as python wrappers. Source: about 1 year ago
  • Machine learning with Julia - Solve Titanic competition on Kaggle and deploy trained AI model as a web service
    This is not a book, but only an article. That is why it can't cover everything and assumes that you already have some base knowledge to get the most from reading it. It is essential that you are familiar with Python machine learning and understand how to train machine learning models using Numpy, Pandas, SciKit-Learn and Matplotlib Python libraries. Also, I assume that you are familiar with machine learning... - Source: dev.to / about 1 year ago
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What are some alternatives?

When comparing Caffe2 and Scikit-learn, you can also consider the following products

TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

MLKit - MLKit is a simple machine learning framework written in Swift.

OpenCV - OpenCV is the world's biggest computer vision library

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

NumPy - NumPy is the fundamental package for scientific computing with Python

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