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PyTorch VS AppDynamics

Compare PyTorch VS AppDynamics and see what are their differences

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  3. » Reviews
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PyTorch logo PyTorch

Open source deep learning platform that provides a seamless path from research prototyping to...

AppDynamics logo AppDynamics

Get real-time insight from your apps using Application Performance Management—how they’re being used, how they’re performing, where they need help.
  • PyTorch Landing page
    Landing page //
    2023-07-15
  • AppDynamics Landing page
    Landing page //
    2023-10-10

PyTorch features and specs

  • Dynamic Computation Graph
    PyTorch uses a dynamic computation graph, which allows for interactive and flexible model building. This is particularly beneficial for researchers who need to modify the network architecture on-the-fly.
  • Pythonic Nature
    PyTorch is designed to be deeply integrated with Python, making it very intuitive for Python developers. The framework feels more 'native' to Python, which improves the ease of learning and use.
  • Strong Community Support
    PyTorch has a large, active, and growing community. This means abundant resources such as tutorials, forums, and third-party tools are available to help developers solve problems and share solutions.
  • Flexibility and Control
    PyTorch offers granular control over computations and provides extensive debugging capabilities. This level of control is beneficial for tasks that require precise tuning and custom implementations.
  • Support for GPU Acceleration
    PyTorch offers seamless integration with GPU hardware, which significantly accelerates the computation process. This makes it highly efficient for deep learning tasks.
  • Rich Ecosystem
    PyTorch has a rich ecosystem including libraries like torchvision, torchaudio, and torchtext, which are specialized for different data types and can significantly shorten development times.

Possible disadvantages of PyTorch

  • Limited Production Deployment Tools
    PyTorch is primarily designed for research rather than production. While deployment tools like TorchServe exist, they are not as mature or integrated as solutions offered by other frameworks like TensorFlow.
  • Lesser Adoption in Industry
    While PyTorch is popular among researchers, it has historically seen less adoption in industry compared to TensorFlow, which means there might be fewer resources for large-scale production deployments.
  • Inconsistent API Changes
    As PyTorch continues to evolve rapidly, occasionally there are breaking changes or inconsistent API updates. This can create maintenance challenges for existing codebases.
  • Steeper Learning Curve for Beginners
    Despite its Pythonic design, PyTorch's focus on flexibility and control can make it slightly harder for beginners to get started compared to some other high-level libraries and frameworks.
  • Less Mature Documentation
    Although the documentation is improving, it has been historically less comprehensive and mature compared to other frameworks like TensorFlow, which can make it difficult to find detailed, clear information.

AppDynamics features and specs

  • Comprehensive Monitoring
    AppDynamics provides end-to-end visibility across applications, infrastructure, and user experience. This helps in identifying performance issues quickly and accurately.
  • Real-time Analytics
    AppDynamics offers real-time monitoring and analytics, which enables immediate detection of anomalies and potential problems before they impact end-users.
  • Ease of Integration
    AppDynamics integrates easily with various platforms, technologies, and third-party services, providing flexibility and extending its usability in diverse environments.
  • Automated Root Cause Analysis
    The platform's advanced algorithms and AI capabilities help in automatically determining the root causes of performance issues, reducing the mean time to resolution.
  • User-friendly Interface
    AppDynamics has an intuitive and user-friendly interface which makes it easier for IT teams to use without extensive training.

Possible disadvantages of AppDynamics

  • Cost
    AppDynamics can be expensive, making it less accessible for smaller organizations or startups with limited budgets.
  • Complexity
    Due to its extensive features and capabilities, the platform can be complex to set up and configure, requiring a significant time investment for initial deployment.
  • Resource Intensive
    The monitoring and analytics processes can be resource-intensive, potentially impacting system performance especially in environments with limited resources.
  • Steep Learning Curve
    Despite its user-friendly interface, mastering the full range of AppDynamics' features and capabilities can take time and necessitate detailed learning.
  • Possible Overhead
    Integrating and running AppDynamics can add additional overhead to the system, which might be an issue in performance-sensitive scenarios.

PyTorch videos

+ Add

PyTorch in 5 Minutes

More videos:

  • Review - Jeremy Howard: Deep Learning Frameworks - TensorFlow, PyTorch, fast.ai | AI Podcast Clips
  • Review - PyTorch at Tesla - Andrej Karpathy, Tesla

AppDynamics videos

+ Add

AppDynamics Acquired for $3.7 Billion | Crunch Report

More videos:

  • Review - AppDynamics CEO Talks Cisco Acquisition | Crunch Report
  • Review - Glassdoor Client Testimonial: AppDynamics

Category Popularity

0-100% (relative to PyTorch and AppDynamics)

PyTorch

AppDynamics

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
Log Management
0 0%
Log Management
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 PyTorch and AppDynamics

PyTorch Reviews

10 Python Libraries for Computer Vision
Similar to TensorFlow and Keras, PyTorch and torchvision offer powerful tools for computer vision tasks. PyTorch’s dynamic computation graph and torchvision’s datasets and pre-trained models make it easy to implement tasks such as image classification, object detection, and style transfer.
Source: clouddevs.com
25 Python Frameworks to Master
Along with TensorFlow, PyTorch (developed by Facebook’s AI research group) is one of the most used tools for building deep learning models. It can be used for a variety of tasks such as computer vision, natural language processing, and generative models.
Source: kinsta.com
Top 8 Alternatives to OpenCV for Computer Vision and Image Processing
PyTorch is another open-source machine learning framework that is widely used in academia and industry. PyTorch provides excellent support for building deep learning models, and it has several pre-trained models for computer vision tasks, making it the ideal tool for several computer vision applications. PyTorch offers a user-friendly interface that makes it easier for...
Source: www.uubyte.com
PyTorch vs TensorFlow in 2022
When we compare HuggingFace model availability for PyTorch vs TensorFlow, the results are staggering. Below we see a chart of the total number of models available on HuggingFace that are either PyTorch or TensorFlow exclusive, or available for both frameworks. As we can see, the number of models available for use exclusively in PyTorch absolutely blows the competition out of...
Source: www.assemblyai.com
15 data science tools to consider using in 2021
First released publicly in 2017, PyTorch uses arraylike tensors to encode model inputs, outputs and parameters. Its tensors are similar to the multidimensional arrays supported by NumPy, another Python library for scientific computing, but PyTorch adds built-in support for running models on GPUs. NumPy arrays can be converted into tensors for processing in PyTorch, and vice...
Source: searchbusinessanalytics.techtarget.com

AppDynamics Reviews

Top 10 Grafana Alternatives in 2024
AppDynamics is an APM tool that enables users to monitor application performance, pinpoint root causes for performance issues, get complete visibility into application ecosystems, extract real-time data insights, and automatically optimize the application environment.
Source: middleware.io
Top 11 Grafana Alternatives & Competitors [2024]
AppDynamics is an enterprise Application Performance Management (APM) solution known for its comprehensive monitoring capabilities. It provides in-depth visibility into application performance and user experiences, offering code-level diagnostics, transaction tracing, and real-time insights.
Source: signoz.io
10 Best Grafana Alternatives [2023 Comparison]
visibility into the health and performance of their applications. As an excellent alternative to Grafana, AppDynamics is particularly renowned for its end-user monitoring (EUM) capabilities, ensuring users are well-informed about end-user errors, issues, crashes, and page-loading details. This enables businesses to tap into valuable insights, swiftly and effortlessly...
Source: sematext.com
10 Best Website Monitoring Services and Tools of 2022
AppDynamics is another website availability monitoring software that helps you detect anomalies and helps you run your business smoothly. The software allows you to track the visual revenue paths with the help of tracked customer or application experience in order to fix the ongoing website issues. Moreover, the tool allows you to monitor every click, swipe, and tap in order...
Source: www.hostingseekers.com
8 Dynatrace Alternatives to Consider in 2021
Cisco’s APM, AppDynamics, is a proactive performance monitoring platform that ensures success for its users, primarily businesses. They focus on observability of the software and application. AppDynamics uses AI-powered insights and focuses on visibility to support application improvement and business performance for their applications.
Source: scoutapm.com

Social recommendations and mentions

Based on our record, PyTorch seems to be more popular. It has been mentiond 133 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.

PyTorch mentions (133)

  • Grasping Computer Vision Fundamentals Using Python
    To aspiring innovators: Dive into open-source frameworks like OpenCV or PyTorch, experiment with custom object detection models, or contribute to projects tackling bias mitigation in training datasets. Computer vision isn’t just a tool, it’s a bridge between the physical and digital worlds, inviting collaborative solutions to global challenges. The next frontier? Systems that don’t just interpret visuals, but... - Source: dev.to / 12 days ago
  • Top Programming Languages for AI Development in 2025
    With the quick emergence of new frameworks, libraries, and tools, the area of artificial intelligence is always changing. Programming language selection. We're not only discussing current trends; we're also anticipating what AI will require in 2025 and beyond. - Source: dev.to / 26 days ago
  • Fine-tuning LLMs locally: A step-by-step guide
    Next, we define a training loop that uses our prepared data and optimizes the weights of the model. Here's an example using PyTorch:. - Source: dev.to / about 2 months ago
  • 10 Must-Have AI Tools to Supercharge Your Software Development
    8. TensorFlow and PyTorch: These frameworks support AI and machine learning integrations, allowing developers to build and deploy intelligent models and workflows. TensorFlow is widely used for deep learning applications, offering pre-trained models and extensive documentation. PyTorch provides flexibility and ease of use, making it ideal for research and experimentation. Both frameworks support neural network... - Source: dev.to / 3 months ago
  • Automating Enhanced Due Diligence in Regulated Applications
    Frameworks like TensorFlow and PyTorch can help you build and train models for various tasks, such as risk scoring, anomaly detection, and pattern recognition. - Source: dev.to / 3 months ago
View more

AppDynamics mentions (0)

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

What are some alternatives?

When comparing PyTorch and AppDynamics, you can also consider the following products

TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.

Dynatrace - Cloud-based quality testing, performance monitoring and analytics for mobile apps and websites. Get started with Keynote today!

Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.

Datadog - See metrics from all of your apps, tools & services in one place with Datadog's cloud monitoring as a service solution. Try it for free.

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

NewRelic - New Relic is a Software Analytics company that makes sense of billions of metrics across millions of apps. We help the people who build modern software understand the stories their data is trying to tell them.

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