Software Alternatives & Reviews

BigML VS Scikit-learn

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

BigML logo BigML

BigML's goal is to create a machine learning service extremely easy to use and seamless to integrate.

Scikit-learn logo Scikit-learn

scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
  • BigML Landing page
    Landing page //
    2022-10-08
  • Scikit-learn Landing page
    Landing page //
    2022-05-06

BigML

Categories
  • Data Science And Machine Learning
  • Technical Computing
  • Data Science Tools
  • Numerical Computation
Website bigml.com
Pricing URL Official BigML Pricing
Details $-

Scikit-learn

Categories
  • Data Science And Machine Learning
  • Data Science Tools
  • Python Tools
  • Software Libraries
Website scikit-learn.org
Pricing URL-
Details $

BigML videos

BigML is Machine Learning for Everyone

More videos:

  • Review - BigML Spring 2016 Webinar - WhizzML!

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 BigML and Scikit-learn)
Data Science And Machine Learning
Data Science Tools
5 5%
95% 95
Technical Computing
100 100%
0% 0
Python 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 BigML and Scikit-learn

BigML 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 seems to be a lot more popular than BigML. While we know about 27 links to Scikit-learn, we've tracked only 2 mentions of BigML. 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.

BigML mentions (2)

  • Free for dev - list of software (SaaS, PaaS, IaaS, etc.)
    Bigml.com — Hosted machine learning algorithms. Unlimited free tasks for development, limit of 16 MB data/task. - Source: dev.to / over 2 years ago
  • Theory: The price action was intentionally manipulated to prevent any AI from being able to predict it. First time this model shows as flat. Forever.
    They know the website is bigml.com it's possible they have many magnitudes better algorithms to predict this shit. And it's also possible they paid some quants to come up with price action that just completely fucks with BigML's algorithm entirely to make it look flat. Source: almost 3 years ago

Scikit-learn mentions (27)

  • 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 / 10 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: 11 months 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: 12 months 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
  • Machine learning with Julia - Solve Titanic competition on Kaggle and deploy trained AI model as a web service
    This is not a book, but only an article. That is why it can't cover everything and assumes that you already have some base knowledge to get the most from reading it. It is essential that you are familiar with Python machine learning and understand how to train machine learning models using Numpy, Pandas, SciKit-Learn and Matplotlib Python libraries. Also, I assume that you are familiar with machine learning... - Source: dev.to / about 1 year ago
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What are some alternatives?

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

RapidMiner - RapidMiner is a software platform for data science teams that unites data prep, machine learning, and predictive model deployment.

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

Qubole - Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.

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

Alteryx - Alteryx provides an indispensable and easy-to-use analytics platform for enterprise companies making critical decisions that drive their business strategy and growth.

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