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Crystal Ball VS Scikit-learn

Compare Crystal Ball VS Scikit-learn and see what are their differences

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Crystal Ball logo Crystal Ball

Crystal Ball provides location based business intelligence through our web based GPS tracking solution. Our product range tracks vehicles, assets, mobile phones and provides lone worker protection solutions on a single platform.

Scikit-learn logo Scikit-learn

scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
  • Crystal Ball Landing page
    Landing page //
    2023-10-17
  • Scikit-learn Landing page
    Landing page //
    2022-05-06

Crystal Ball videos

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where to hang crystal ball in home | crystal ball | how to use crystal ball in home

More videos:

  • Tutorial - How To Use A Crystal Ball For SCRYING 🔮👀 (Tips For Beginners)

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.

Category Popularity

0-100% (relative to Crystal Ball and Scikit-learn)

Crystal Ball

Scikit-learn

Business Intelligence
100 100%
Business Intelligence
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Data Dashboard
9 9%
Data Dashboard
91% 91
Data Science Tools
0 0%
Data Science Tools
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 Crystal Ball and Scikit-learn

Crystal Ball 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...
Source: searchbusinessanalytics.techtarget.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.

Crystal Ball mentions (0)

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

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 / 2 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 / 11 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: 12 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: 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
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What are some alternatives?

When comparing Crystal Ball 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.

SAP BusinessObjects Predictive Analytics - SAP Predictive Analytics software allows the user to create better and faster predictive results, deliver machine learning at scale using a factory approach and bring predictive insights where people interact _ in business processes and applications.

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

Board - Unified BI, CPM and predictive analytics software.

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

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