Software Alternatives, Accelerators & Startups

SocialOomph VS Scikit-learn

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

SocialOomph logo SocialOomph

Boost your productivity with advanced post scheduling tools. We help individuals and teams.

Scikit-learn logo Scikit-learn

scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
  • SocialOomph Landing page
    Landing page //
    2021-10-09
  • Scikit-learn Landing page
    Landing page //
    2022-05-06

SocialOomph videos

Buffer vs Later vs HootSuite vs SocialOomph vs Sprout Social (Best Social Media Scheduling App?)

More videos:

  • Review - Socialoomph Review - Using Socialoomph for SEO

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 SocialOomph and Scikit-learn)
Social Media Tools
100 100%
0% 0
Data Science And Machine Learning
Social Media Marketing
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 SocialOomph and Scikit-learn

SocialOomph Reviews

11 of The Best Unfollow Twitter Tools
SocialOomph: SocialOomph is a social media automation tool for your Twitter account. It offers you the ability to automatically follow, unfollow and send tweets to people who do not follow you back and do much more!
Source: loriballen.com
6 Hootsuite Alternatives That You Should Explore in 2020
Hence, it was previously known as TweetLater.com. However, slowly and steadily it also started looking at improving the overall productivity of different social media sites and changed its name to SocialOomph.
6 Hootsuite Alternatives You Must Try
SocialOomph, another alternative with features like HootSuite, was originally built to focus on Twitter only. In 2009, this Canadian-based web app expanded into other social media networks like Facebook, RSS, WordPress, App.net and Plurk. In many ways, SocialOomph is similar to Hootsuite, like scheduling and updating posts, and analytics updates. The scheduling features of...
Source: sprout24.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...

Social recommendations and mentions

Based on our record, Scikit-learn seems to be more popular. 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.

SocialOomph mentions (0)

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

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 / 20 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 SocialOomph and Scikit-learn, you can also consider the following products

SproutSocial - Sprout Social is a social media management tool created to help businesses find new customers & grow their social media presence. Try it for free.

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

Buffer - Buffer makes it super easy to share any page you're reading. Keep your Buffer topped up and we automagically share them for you through the day.

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

HootSuite - Enhance your social media management with Hootsuite, the leading social media dashboard. Manage multiple networks and profiles and measure your campaign results.

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