Software Alternatives, Accelerators & Startups

Enchant VS Scikit-learn

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

Enchant logo Enchant

The easiest way to scale personalized customer support

Scikit-learn logo Scikit-learn

scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
  • Enchant Landing page
    Landing page //
    2022-07-04
  • Scikit-learn Landing page
    Landing page //
    2022-05-06

Enchant videos

Enchantcloset.com Review: Beware Of Enchant Closet Scam!

More videos:

  • Review - Harman Kardon Enchant 800 Soundbar "MultiBeam" 8 Channel Surround Sound - REVIEW
  • Review - Top Fin Enchant 2 Year Review

Scikit-learn videos

Learning Scikit-Learn (AI Adventures)

More videos:

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

Category Popularity

0-100% (relative to Enchant and Scikit-learn)
Help Desk
100 100%
0% 0
Data Science And Machine Learning
Customer Support
100 100%
0% 0
Data Science Tools
0 0%
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 Enchant and Scikit-learn

Enchant 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...

Social recommendations and mentions

Based on our record, Scikit-learn should be more popular than Enchant. It has been mentiond 29 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.

Enchant mentions (4)

  • Ask HN: PG's 'Do Things That Don't Scale' Manual Examples
    At Enchant (https://enchant.com): - We launched without billing. Early customers used the product for free until we eventually built out billing - We offer data imports from competitors. It's a semi-automated process - sometimes there's existing working code, sometimes it needs tweaking, sometimes it gets written as part of the process. Either way, it's a win if it helps someone make a purchase decision. - We... - Source: Hacker News / 8 months ago
  • Ask HN: Who's using Ruby web development without Ruby on Rails (RoR)?
    We[0] use Ruby without Rails - Sinatra for the most part. I started the codebase over a decade ago now, and at the time Rails felt a little heavy (inline with your comments). That said, Rails does let you get started pretty quickly without needing much of anything else. Rails has more magic. If you prefer less magic, then Sinatra is the way. https://enchant.com. - Source: Hacker News / over 1 year ago
  • How to offer effective free trials
    For our own SaaS[0], we provide a timed trial. But we regularly provide trial extensions because reality of business is that it takes time to get everybody on board and onboarded. Reading this post, I suspect '30 days of use' would result in less 'please extend the trial' emails and would mean less friction during the trial. However, there is a tradeoff: when somebody reaches out for a trial extension, it may be... - Source: Hacker News / almost 2 years ago
  • Ask HN: What made your business take off that you wish you'd done much earlier?
    In the space we[1] operate, there's no shortage of competitors. Over the years, I've seen that those who can unlock marketing see a lot more success, even with a shittier product. As a developer-turned-founder, a lot of marketing feels sleazy. Was it always this way? So much link-bait, fluffy posts that are really big ads, shallow content just for SEO, upvoting-rings on platforms, etc. There's so few who seem to... - Source: Hacker News / over 2 years ago

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 / 13 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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What are some alternatives?

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

Zendesk - Zendesk is a beautiful, lightweight help-desk solution.

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

Freshdesk - Freshdesk is a cloud-based customer support software that lets you support customers through traditional channels like phone and email, social channels like Facebook and Twitter, and your own branded community

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

HelpScout - Help Scout is a simple, straightforward way to provide excellent support

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