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Zylo VS Scikit-learn

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

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Powerful SaaS integration toolkit for SaaS developers - create, amplify, manage and publish native integrations from within your app with Cyclr's flexible Embedded iPaaS. featured
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Zylo logo Zylo

Zylo helps organizations optimize their SaaS investments by providing insights around Spend, Utilization, and User Feedback.

Scikit-learn logo Scikit-learn

scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
  • Zylo Landing page
    Landing page //
    2023-09-27
  • Scikit-learn Landing page
    Landing page //
    2022-05-06

Zylo features and specs

  • Comprehensive SaaS Management
    Zylo offers a robust platform to discover, manage, and optimize SaaS subscriptions, providing visibility into all applications across an organization.
  • Cost Optimization
    The platform helps organizations reduce software spend by identifying unused licenses and redundant applications, ultimately driving cost efficiencies.
  • User-friendly Interface
    Zylo's interface is designed to be intuitive and easy to navigate, allowing users to quickly access key information and insights.
  • Integration Capabilities
    Zylo supports integrations with numerous popular SaaS applications and systems, enabling seamless data aggregation and management.
  • Enhanced Compliance
    The platform aids in ensuring compliance with licensing agreements and regulatory requirements by providing detailed usage and contract data.

Possible disadvantages of Zylo

  • Cost
    Zylo may come with a considerable subscription fee, which might be a significant investment for small to medium-sized businesses.
  • Complexity of Setup
    Initial setup and integration with existing systems can be complex and time-consuming, requiring significant effort from IT teams.
  • Learning Curve
    While the interface is user-friendly, fully leveraging all features and functionalities of the platform may require training and time.
  • Dependency on Accurate Data
    The effectiveness of Zylo heavily depends on the accuracy and completeness of the data input, which can be a challenge if data is fragmented or inconsistent.
  • Limited Offline Access
    Zylo is a web-based solution, so it requires an internet connection to access. This might limit its usability in environments with poor connectivity.

Scikit-learn features and specs

  • Ease of Use
    Scikit-learn provides a high-level interface for common machine learning algorithms, making it easy for beginners and professionals to implement complex models with minimal coding.
  • Extensive Documentation and Community Support
    The library has comprehensive documentation and a large, active community. This makes it easy to find tutorials, examples, and solutions to common problems.
  • Integration with Other Libraries
    Scikit-learn integrates well with other scientific computing libraries such as NumPy, SciPy, and pandas, allowing for seamless data manipulation and analysis.
  • Variety of Algorithms
    It offers a wide array of machine learning algorithms for tasks such as classification, regression, clustering, and dimensionality reduction.
  • Performance
    Designed with performance in mind, many of the algorithms are optimized and some even support multicore processing.

Possible disadvantages of Scikit-learn

  • Limited Deep Learning Support
    Scikit-learn is primarily focused on traditional machine learning algorithms and does not offer support for deep learning models, unlike libraries like TensorFlow or PyTorch.
  • Not Ideal for Large-Scale Data
    While Scikit-learn performs well for moderate-sized datasets, it may not be the best choice for extremely large datasets or big data applications.
  • Lack of Online Learning Algorithms
    The library has limited support for online learning algorithms, which are useful for scenarios where data arrives in a stream and model needs to be updated incrementally.
  • Less Flexibility in Customization
    It can be less flexible compared to lower-level libraries when highly customized or specific implementations are needed.
  • Dependency Overhead
    Scikit-learn relies on several other Python libraries like NumPy and SciPy, which might require users to manage multiple dependencies.

Analysis of Zylo

Overall verdict

  • Zylo is generally considered a good choice for organizations looking to manage and optimize their SaaS portfolios. It offers valuable tools and insights to help companies gain control over their SaaS environments, which can lead to significant cost savings and operational improvements.

Why this product is good

  • Zylo is a prominent SaaS management platform that helps enterprises manage and optimize their software-as-a-service (SaaS) subscriptions. It is known for providing comprehensive visibility into SaaS usage and spending, allowing businesses to make informed decisions and reduce inefficiencies. With features such as application discovery, spend management, and data-driven insights, Zylo aims to streamline SaaS operations and enhance overall productivity.

Recommended for

  • Large enterprises with multiple SaaS subscriptions
  • Organizations looking to optimize software spending
  • IT departments focused on improving software governance
  • Companies aiming to enhance visibility into SaaS usage and reduce redundancy

Analysis of Scikit-learn

Overall verdict

  • Yes, Scikit-learn is generally regarded as a good library for machine learning, especially for beginners and intermediate users who need reliable tools with efficient implementation of numerous algorithms.

Why this product is good

  • Scikit-learn is considered a good machine learning library because it provides a wide range of state-of-the-art algorithms for supervised and unsupervised learning. It is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy. The library is well-documented, easy to use, and has a consistent API that simplifies the integration of different algorithms. Furthermore, there's a strong community and continuous development, which means it is well-maintained and updated regularly with new features and improvements.

Recommended for

  • Beginners learning machine learning concepts and application.
  • Data scientists and engineers looking for a robust and efficient toolkit to build and deploy machine learning models.
  • Researchers who need an easy-to-use library that facilitates the experimentation of various algorithms.
  • Developers who require a seamless, Python-based machine learning library that integrates well with other data analysis tools and environments.

Zylo videos

+ Add

Sony Ericsson Zylo Review

More videos:

  • Review - X-zylo review 600+ft!!!
  • Demo - X Zylo Review and Demo! Is it Magic?

Scikit-learn videos

+ Add

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 Zylo and Scikit-learn)

Zylo

Scikit-learn

SaaS Management
100 100%
SaaS Management
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Subscription Management
100 100%
Subscription Management
0% 0
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 Zylo and Scikit-learn

Zylo 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 should be more popular than Zylo. It has been mentiond 31 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.

Zylo mentions (4)

  • Any Experience with Zylo or Torri
    Hi we want to decrease our cost of saas tools and thinking of buying saas manmagement platform. Short list is zylo and torri. https://zylo.com. - Source: Hacker News / about 2 years ago
  • Too much software - can this help
    Something similar to this already exists. Source: almost 3 years ago
  • Annoying problems to solve
    It's also called "SaaS management" or "software asset management" e.g. zylo.com bettercloud.com or blissfully.com. Source: over 3 years ago
  • Losing control and track of SaaS applications.
    I'm coming from the perspective of a smaller-medium sized business, so something really comprehensive/expensive like Zylo or Bettercloud might be overkill or simply not affordable unless you are enterprise-sized. For bigger companies though, it's the perfect solution and there are a lot of helpful features for big orgs. Source: over 3 years ago

Scikit-learn mentions (31)

  • Must-Know 2025 Developer’s Roadmap and Key Programming Trends
    Python’s Growth in Data Work and AI: Python continues to lead because of its easy-to-read style and the huge number of libraries available for tasks from data work to artificial intelligence. Tools like TensorFlow and PyTorch make it a must-have. Whether you’re experienced or just starting, Python’s clear style makes it a good choice for diving into machine learning. Actionable Tip: If you’re new to Python,... - Source: dev.to / 4 months ago
  • 🚀 Launching a High-Performance DistilBERT-Based Sentiment Analysis Model for Steam Reviews 🎮🤖
    Scikit-learn (optional): Useful for additional training or evaluation tasks. - Source: dev.to / 5 months ago
  • 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 / 12 months 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 / about 1 year 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 / almost 2 years ago
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What are some alternatives?

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

Torii - SaaS Management Software.

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

Blissfully - Blissfully offers solutions to track, manage, and optimize SaaS spendings.

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

Cledara - We help companies bring visibility and control to their ever-growing #SaaS stack.

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

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