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Scikit-learn VS Pastel

Compare Scikit-learn VS Pastel 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
Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Scikit-learn logo Scikit-learn

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

Pastel logo Pastel

Sticky note-based feedback collection tool for live websites
  • Scikit-learn Landing page
    Landing page //
    2022-05-06
  • Pastel Landing page
    Landing page //
    2022-09-23

Scikit-learn videos

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Learning Scikit-Learn (AI Adventures)

More videos:

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

Pastel videos

+ Add

Soft pastel review Jackson's, Unison, Rembrandt, etc

More videos:

  • Review - What Pastels Should I Buy?
  • Demo - Mungyo Soft Pastel 64 set review and pastel demonstration

Category Popularity

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

Scikit-learn

Pastel

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Customer Feedback
0 0%
Customer Feedback
100% 100
Data Science Tools
100 100%
Data Science Tools
0% 0
User Feedback
0 0%
User Feedback
100% 100

User comments

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Reviews

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

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

Pastel Reviews

We have no reviews of Pastel yet.
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Social recommendations and mentions

Based on our record, Scikit-learn seems to be a lot more popular than Pastel. While we know about 29 links to Scikit-learn, we've tracked only 2 mentions of Pastel. 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.

Scikit-learn mentions (29)

  • Essential Deep Learning Checklist: Best Practices Unveiled
    How to Accomplish: Utilize data splitting tools in libraries like Scikit-learn to partition your dataset. Make sure the split mirrors the real-world distribution of your data to avoid biased evaluations. - Source: dev.to / 17 days ago
  • 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 / 4 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 / about 1 year 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
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Pastel mentions (2)

What are some alternatives?

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

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

Iterate - Get the feedback you need to build better products

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

BugHerd - BugHerd: The Website Feedback Tool for Agencies

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

Usersnap - Usersnap is a customer feedback software for SaaS companies that need to constantly improve and grow their products.

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