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Scikit-learn VS Flookup

Compare Scikit-learn VS Flookup 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:
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  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.

Flookup logo Flookup

Fuzzy lookup, highlight and remove duplicates from your datasets
  • Scikit-learn Landing page
    Landing page //
    2022-05-06
  • Flookup Landing page
    Landing page //
    2020-11-16

Flookup is lightweight data cleaning suite for Google Sheets. It can be used to:

  • Remove duplicates based on text similarity
  • Highlight duplicates based on text similarity
  • Fuzzy lookup or merge data
  • Extract unique values from fuzzy duplicates
  • Calculate percentage similarities between text entries
  • Remove unwanted words, diacritics and punctuation marks

Scikit-learn

Website
scikit-learn.org
Pricing URL
-
$ Details
Platforms
-
Release Date
-
Edit details

Flookup

Website
getflookup.com
Pricing URL
Official Flookup Pricing
$ Details
paid Free Trial $10.0 / Monthly (Flookup Standard | 01 User)
Platforms
Browser Web Cross Platform
Release Date
2018 April
Edit details

Scikit-learn features and specs

No features have been listed yet.

Flookup features and specs

  • Unlimited data ingestion: Yes
  • Fuzzy matching: Yes
  • Removing duplicates: Yes
  • Highlighting duplicates: Yes

Scikit-learn videos

+ Add

Learning Scikit-Learn (AI Adventures)

More videos:

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

Flookup videos

No Flookup videos yet. You could help us improve this page by suggesting one.

+ Add video

Category Popularity

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

Scikit-learn

Flookup

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Data Cleansing
0 0%
Data Cleansing
100% 100
Data Science Tools
100 100%
Data Science Tools
0% 0
Spreadsheets
0 0%
Spreadsheets
100% 100

Questions and Answers

As answered by people managing Scikit-learn and Flookup.

Which are the primary technologies used for building your product?

Flookup's answer:

  • Google Apps Script
  • Google Sheets
  • Google Firebase

Why should a person choose your product over its competitors?

Flookup's answer:

  • It comes with built-in privacy.
  • It is very fast and efficient.
  • It is easy to use and intuitive.
  • It is safe to use with its instant "backup and restore" feature-by-affiliation.
  • It comes with a lifetime of upgrades.
  • It is very affordable.

What's the story behind your product?

Flookup's answer:

Flookup was created out of necessity. I was part of a team working on a project that involved cleaning and standardising thousands of rows of data. This data was some of the "dirtiest" we had ever come across and the process of cleaning it usually took about a week for each team member to complete manually. It took a few attempts but, eventually, I was able to develop a usable version of Flookup... and its impact was so significant that our task times were reduced to an average of 30 minutes, with our error rate never exceeding 1% after that.

How would you describe your primary audience?

Flookup's answer:

  • Data Analysts
  • Data Scientists
  • Statisticians
  • Librarians
  • Data Entry Clerks
  • Sales professionals

Who are some of the biggest customers of your product?

Flookup's answer:

  • ComX
  • Shopify
  • Salesforce
  • Zillow

What makes your product unique?

Flookup's answer:

Flookup features an intuitive set of functions and a finetuned fuzzy matching algorithm capable of tackling the most challenging and untidy datasets found online. It has excelled not only in Western projects but also in projects across Africa, South America and even those involving Asian languages like Chinese.

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 Flookup

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

Flookup Reviews

  1. Great time saver!

    Flookup helps complete laborious fuzzy matching or lookup tasks quickly and efficiently. It is also the most affordable deduping solution online; useful for removing or highlighting duplicates from mailing lists, contacts and leads.

    🏁 Competitors: FuzzyWuzzy
    👍 Pros:    Fast|Easy to use|Accurate|Dynamic
    👎 Cons:    Requires an internet connection
HIGHLIGHTING DUPLICATES: GOOGLE SHEETS VS FLOOKUP
The result will be duplicates that have been identified despite differences in spelling. Please note that you can also choose to highlight duplicates by sound similarity by clicking Extensions > Flookup > Highlight duplicates > By sound and following steps similar to the ones above.
Source: www.getflookup.com

Social recommendations and mentions

Based on our record, Scikit-learn seems to be more popular. It has been mentiond 28 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.

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
View more

Flookup mentions (0)

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

What are some alternatives?

When comparing Scikit-learn and Flookup, 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.

FuzzyWuzzy - FuzzyWuzzy is a Fuzzy String Matching in Python that uses Levenshtein Distance to calculate the differences between sequences.

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

Google Sheets + MonkeyLearn - Power up your Google Sheets with text analysis

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

SheetHacks by Polymer Search - Discover the best tips & tricks for Google Sheets & Excel

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