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Scikit-learn VS NinjaOne

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

Atera
Atera is reinventing the world of IT by harnessing AI to power our all-in-one Remote Monitoring and Management (RMM), Helpdesk, Ticketing, and automations platform—streamlining organizational IT management at scale with our proprietary Action AI™. featured
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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.

NinjaOne logo NinjaOne

NinjaOne (Formerly NinjaRMM) provides remote monitoring and management software that combines powerful functionality with a fast, modern UI. Easily remediate IT issues, automate common tasks, and support end-users with powerful IT management tools.
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  • Scikit-learn Landing page
    Landing page //
    2022-05-06
  • NinjaOne
    Image date //
    2024-02-01

NinjaOne automates the hardest parts of IT, empowering more than 17,000 IT teams with visibility, security, and control over all endpoints. The NinjaOne platform increases productivity while reducing risk and IT costs. Organizations use NinjaOne, including its wide range of IT and security integrations, for use cases including endpoint management, patch management, mobile device management, software deployment, remote access, endpoint backup, and more.

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.

NinjaOne features and specs

  • Self Service Portal
  • Audit, Analysis and Compliance
  • User Activity Monitoring
  • Software Inventory
  • Internet Usage Monitoring
  • IP Address Monitoring
  • Bandwidth Monitoring
  • Network Diagnosis
  • Vulnerability Scanners
  • Data Loss Prevention
  • Multi-Patch Deployments
  • Unified Threat Management (UTM)
  • Ransomware Protection
  • Intrusion Detection and Prevention (IDS/IPS)
  • Endpoint Detection and Response
  • Breach Detection
  • Advanced Threat Protection

Scikit-learn videos

+ Add

Learning Scikit-Learn (AI Adventures)

More videos:

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

NinjaOne videos

+ Add

NinjaRMM Live Setup

More videos:

  • Review - NinjaRMM Tech Talk
  • Demo - NinjaOne Backup
  • Review - TechnologyAdvice: NinjaOne Review - Top Features, Pros & Cons, and Alternatives
  • Demo - NinjaOne | Spend more time on the important things
  • Review - NinjaOne RMM Review

Category Popularity

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

Scikit-learn

NinjaOne

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Monitoring Tools
0 0%
Monitoring Tools
100% 100
Data Science Tools
100 100%
Data Science Tools
0% 0
IT Management
0 0%
IT Management
100% 100

Questions and Answers

As answered by people managing Scikit-learn and NinjaOne.

How would you describe your primary audience?

NinjaOne's answer:

NinjaOne customers include MSPs and internal IT organizations of all sizes.

What makes your product unique?

NinjaOne's answer:

NinjaOne is a cloud-native unified IT management platform tailored for IT organizations and MSPs. It offers comprehensive monitoring, management, patching and security for a diverse range of endpoints — including Windows, macOS, Linux, VMs, and SNMP — all consolidated within a singular intuitive dashboard.

Its robust automation features empower technicians to offload routine, time-intensive tasks, redirecting their attention to strategic endeavors. Designed for proactive daily management, NinjaOne boasts a user-friendly interface, ensuring a smooth set-up and operation. With complimentary unlimited onboarding, training, and support, we're committed to maximizing the ROI for our customers' NinjaOne investments.

Why should a person choose your product over its competitors?

NinjaOne's answer:

NinjaOne equips MSP and IT teams with a unified hub for overseeing, patching, and supporting all their endpoints. Leveraging our integrated solution and policy-driven management, we introduce a remarkable degree of automation into standard IT workflows, enabling technicians to channel their expertise into intricate tasks and innovative problem-solving.

Tailored for the modern, distributed workforce, NinjaOne's cloud-native platform allows technicians to manage any internet-connected endpoint from any location, eliminating the need for any infrastructure. This not only trims management costs but also simplifies the process. The platform's agile and user-friendly interface further amplifies efficiency, making IT operations seamless for teams.

What's the story behind your product?

NinjaOne's answer:

NinjaOne is dedicated to building top-tier, scalable, and user-friendly IT management solutions that empower MSPs and IT experts to ensure business continuity and enhance profitability. With a user experience intricately designed from inception, we aim to minimize onboarding costs and optimize automation, offering a cutting-edge, proactive IT management journey. Presently, over 13,000 MSPs and IT entities worldwide trust NinjaOne to oversee, update, and secure more than 5 million endpoints.

Which are the primary technologies used for building your product?

NinjaOne's answer:

NinjaOne is a cloud-native unified IT management platform. Key technologies include monitoring & alerting, patch management, software deployment, scripting & automation, remote control, backup, ticketing, documentation, next generation antivirus (NGAV) and endpoint detection and response (EDR). Additionally, NinjaOne seamlessly integrates with numerous popular solutions, further enhancing our customers' workflow efficiency.

User comments

Share your experience with using Scikit-learn and NinjaOne. For example, how are they different and which one is better?
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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 NinjaOne

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

NinjaOne Reviews

12 Best Asset Management Software For IT Teams In 2023
Why I picked NinjaOne: I like how the tool offers a complete toolkit for small IT teams and IT managers to manage, monitor, secure, and improve servers, network devices, laptops, and workstations. I think the best part of the platform is just how easy it is to use even if you have a wide variety of clients or IT to manage.
Source: thectoclub.com
10 Best RMM Software | Remote Monitoring & Management Tools 2021
NinjaRMM Pricing: NinjaRMM offers a free trial of their product. Ninja is priced on a per-device basis based on the features needed.
Source: www.softwaretestinghelp.com
12 Best RMM Software and Tools for 2021
NinjaRMM is an excellent RMM solution with real-time monitoring for Windows and Mac computers. NinjaRMM offers users the ability to automate patches to remote networks. The software supports over 120 applications including Java and Dropbox. Patching these popular services allows you to minimize the vulnerabilities your users face.
Source: www.comparitech.com
8 Best RMM Software and Tools
NinjaRMM’s monitoring agent can be installed on Windows and Mac computers and provides endpoint data including, processing, memory, utilization, network, logs, etc. Additionally, NinjaRMM’s automation capabilities allow managers to check the entire infrastructure, install patches, etc.
Source: www.pcwdld.com
Best helpdesk software of 2020: for ticketing and support
NinjaRMM is a cloud-based help desk solution that allows you to monitor everything in real-time. The GUI is simple and easy to use, which can make the learning curve in setting up, using, and customizing short and sweet. The developers are also proactively adding additional features, not least to increase the number of available integrations and improving the available toolkit.
Source: www.techradar.com

Social recommendations and mentions

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

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 / 11 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
View more

NinjaOne mentions (0)

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

What are some alternatives?

When comparing Scikit-learn and NinjaOne, 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.

Atera - Atera is reinventing the world of IT by harnessing AI to power our all-in-one Remote Monitoring and Management (RMM), Helpdesk, Ticketing, and automations platform—streamlining organizational IT management at scale with our proprietary Action AI™.

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

ConnectWise Automate - Solve IT Problems with ConnectWise Automate, Remote Monitoring and Remote Management Software. Visit to boost the effectiveness of your IT teams.‎Try ConnectWise Automate .

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

Microsoft Operations Management Suite - Microsoft Operations Management Suite enables user to gain visibility and control across the hybrid cloud with simplified operations management and security

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