Spyder VS Scikit-learn

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

LibHunt

LibHunt tracks mentions of software libraries on relevant social networks. Based on that data, you can find the most popular projects and their alternatives. featured

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Spyder

The Scientific Python Development Environment

Scikit-learn

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

Landing page //
2023-08-06

Landing page //
2022-05-06

First steps with Spyder - Part 1: Getting Started

Scikit-learn videos

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Learning Scikit-Learn (AI Adventures)

Category Popularity

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

Scikit-learn

Text Editors

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Text Editors

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Data Science And Machine Learning

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Data Science And Machine Learning

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IDE

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IDE

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Data Science Tools

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User comments

Share your experience with using Spyder and Scikit-learn. For example, how are they different and which one is better?

Reviews

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

If you have the Anaconda distribution installed on your computer, you probably already know Spyder. It’s an open source cross-platform IDE for data science. If you have never worked with an IDE, Spyder could perfectly be your first approach. It integrates the essentials libraries for data science, such as NumPy, SciPy, Matplotlib and IPython, besides that, it can be extended...

Source: www.datacamp.com

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 a lot more popular than Spyder. While we know about 28 links to Scikit-learn, we've tracked only 2 mentions of Spyder. 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.

Spyder mentions (2)

GitHub announced the 20 projects selected for their accelerator first cohort
- https://github.com/spyder-ide/spyder: The scientific Python development environment - https://github.com/strawberry-graphql/strawberry: A GraphQL library for Python that leverages type annotations. Source: about 1 year ago
Python GUI Programming
Spyder is open source and I was going through the source code. It is a lot to take in and before I go through the code I wanted to ask if anyone could point me in the direction of a Spyder code skeleton. Source: about 1 year ago

Scikit-learn mentions (28)

How to Build a Logistic Regression Model: A Spam-filter Tutorial
Online Courses: Coursera: "Machine Learning" by Andrew Ng EdX: "Introduction to Machine Learning" by MIT Tutorials: Scikit-learn documentation: https://scikit-learn.org/ Kaggle Learn: https://www.kaggle.com/learn Books: "Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow" by Aurélien Géron "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani, and Jerome Friedman By... - Source: dev.to / 3 months ago
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 / 12 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: about 1 year 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: about 1 year 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