PyTorch VS Embeddable

Compare PyTorch VS Embeddable and see what are their differences

Rating: 0 reviews
Pricing: Open source

Rating: 0 reviews
Pricing: Paid

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Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Which is more popular?

Based on our record, PyTorch seems to be a lot more popular than Embeddable. While we know about 144 links to PyTorch, we've tracked only 2 mentions of Embeddable.

social mentions: 144 vs 2
Data Science And Machine Learning popularity: 100% vs 0%
alternatives listed: 240+ vs 165

Base details

Website, pricing, platforms and company facts side by side.

	PyTorch	Embeddable
Website	pytorch.org	embeddable.com
Pricing	Open source	Paid
Company	—	Startup from the United Kingdom · 20 - 49 employees · 2023
Listed in	Data Science And Machine Learning AI Data Science Tools Python Tools +1	Embedded Analytics Dashboard Software Data Visualization Business Intelligence Data Dashboard Customer-facing Analytics Data Analysis Data Analytics Reporting Platform Reporting & Dashboard +7

About PyTorch and Embeddable

In their own words, as submitted to SaaSHub.

PyTorch

Embeddable

No description of PyTorch yet.

Build Remarkable Analytics Experiences. No more 'Build vs. Buy'. Embeddable is the embedded analytics tool where you own the front-end code and we handle everything else. Now you can build fully-bespoke, fast-loading charts and dashboards in your app without the engineering costs. Delight your...

Features and specs

What each product offers, as listed by its team.

PyTorch 6 features

Embeddable 14 features

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

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.

Cloud-Hosted Option
Self-Hosted Option
Frontend SDK
No-code Dashboard Builder
Performant Embedding
Row-Level Security
Configurable Cache
Compatible with Major Databases
Compatible with Charting Libraries
Template Charting Components Provided
Included
Dedicated Account Management
Version Control
Audit Logs
Documentation

Analysis

An editorial look at what each product does well and who it suits.

PyTorch

Embeddable

Overall verdict

Yes, PyTorch is considered a good deep learning framework.

Why this product is good

Ease of Use: PyTorch has an intuitive interface that makes it easier to learn and use, especially for beginners.
Dynamic Computation Graphs: PyTorch employs dynamic computation graphs, which provide more flexibility in building and modifying models on the fly.
Strong Community and Support: PyTorch has a large and active community, offering extensive resources, forums, and tutorials.
Research Adoption: PyTorch is widely adopted in the research community, making state-of-the-art models and techniques readily available.
Integration: PyTorch integrates well with other libraries and tools in the Python ecosystem, providing robust support for various applications.

Recommended for

Researchers and Academics: Ideal for those who need a flexible and dynamic tool for experimenting with new models and techniques.
Industry Practitioners: Suitable for developers and data scientists working on production-level machine learning solutions.
Educators and Learners: Great for educational purposes due to its easy-to-understand syntax and comprehensive documentation.

No analysis of Embeddable yet.

Videos

Walkthroughs and reviews on video.

PyTorch 3 videos + Add

Embeddable 0 videos + Add

PyTorch in 5 Minutes

Category popularity

How often each product is chosen within a category, 0–100% relative to the other.

Score bands 0–20 21–40 41–50 51–60 61–100

PyTorch

Embeddable

100% 100%

Data Science And Machine Learning

0% 0%

Data Dashboard

100% 100%

Data Science Tools

0% 0%

Business Intelligence

100% 100%

Questions & Answers

As answered by people managing PyTorch and Embeddable.

How would you describe the primary audience of your product?

Embeddable's answer:

Software companies who care about the UX and loading speed of their customer-facing analytics.

What makes your product unique?

Embeddable's answer:

Get the best of 'Build vs. Buy' in one stack-agnostic solution. Embeddable gives you full control over the frontend of your analytics experience, and handles the backend for you. No longer do you have to choose between a limited out-of-the-box solution, or building everything from scratch.

What's the story behind your product?

Embeddable's answer:

Embeddable is from the team behind Trevor.io -- a popular internal BI tool which also allows you to embed dashboards into your app. We realised embedding dashboards from a BI tool into your app wasn't the 'dream solution', and building analytics from scratch was super expensive... so we built Embeddable from the ground up to enable teams to deliver fully-bespoke, highly-performant analytics in their apps for their customers in 10% of the time.

Who are some of the biggest customers of your product?

Embeddable's answer:

Scalapay
Adthena
Irwin
EtonX
Resident Advisor
Facilities Solutions Group (FSG)
Multibrain
Raydiant
ThinkCERCA
Tixly
Softools
Faheem App
Just Move In
Any Creek

Why should a person choose your product over its competitors?

Embeddable's answer:

If you want full control over the UX of your customer-facing analytics experience, but don't want to invest months of developer time on building and maintaining a fully-custom build -- OR -- if you're using an embedded analytics too already that loads slowly and doesn't look and feel like the rest of your platform.

User comments

Share your experience with using PyTorch and Embeddable. For example, how are they different and which one is better?

Reviews and articles

External articles and on-site reviews we used to compare the two products.

PyTorch no reviews yet

Embeddable no reviews yet

10 Python Libraries for Computer Vision
clouddevs.com · Jan 2024

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...
25 Python Frameworks to Master
kinsta.com · Oct 2023

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...
Top 8 Alternatives to OpenCV for Computer Vision and Image Processing
www.uubyte.com · Jul 2023

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...

6 Best Looker alternatives
trevor.io · Jun 2024

After a successful, oversubscribed Private Beta, Embeddable is now publicly available. More information on how to work with Embeddable can be found on their homepage at embeddable.com. Get in touch with the Embeddable...
Power BI Embedded vs Looker Embedded: Everything you need to know
embeddable.com · Nov 2023

The main differences between Power BI Embedded and Embeddable are performance, price, and customizability. Embeddable gives you full control over your charting components and data models. It’s also built from the...
Embedded analytics in B2B SaaS: A comparison
medium.com · Nov 2023

I’m happy to say that we’ve enrolled in the beta program of Embeddable. After learning all the above it seems like this is the option we’d want to invest in. We’ll keep you posted on how this pans out, but we’re...

Social recommendations and mentions

Recommendations tracked on public social media and blogs since March 2021.

PyTorch 144 mentions

Embeddable 2 mentions

Developer Take On: A High-Resolution Neural Cellular Automata
PyTorch: A popular deep learning framework for Python. - Source: dev.to / 3 months ago
Where to Get Hands-On AI Training for Cybersecurity Professionals
Pre-configured environment. A good course ships a VM or container with Jupyter, pandas, scikit-learn, PyTorch or transformers, and realistic security datasets loaded. GTK Cyber students work in the Centaur VM, a free Apache 2.0 portable... - Source: dev.to / 4 months ago
Running AI Models on GPU Cloud Servers: A Beginner Guide
Install PyTorch with GPU support: Go to the official PyTorch website (pytorch.org) and use their configurator to get the correct pip or conda command for your specific CUDA version. It will look something like this:. - Source: dev.to / 5 months ago

AI in BI tools: why we're not there yet
Then comes data modeling. BI tools such as Embeddable need to know how different tables and fields relate to each other. Someone has to define what terms like “top customer” or “Q3 revenue” actually mean. Without this, the AI won't know... - Source: dev.to / over 1 year ago
Apache Superset
It’s still pretty new but build by an experienced team. It’s commercial software though. https://embeddable.com/. - Source: Hacker News / over 2 years ago

Alternatives to PyTorch and Embeddable

When comparing PyTorch and Embeddable, 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.

Compare TensorFlow to PyTorch or Embeddable:

TensorFlow vs PyTorch TensorFlow vs Embeddable
Luzmo
From data to decisions, damn fast. Embed beautiful, easy-to-use dashboards in your SaaS product in days, not months.

Compare Luzmo to PyTorch or Embeddable:

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

Compare Keras to PyTorch or Embeddable:

Keras vs PyTorch Keras vs Embeddable
Metabase
Metabase is the easy, open source way for everyone in your company to ask questions and learn from...

Compare Metabase to PyTorch or Embeddable:

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

Compare Scikit-learn to PyTorch or Embeddable:

Scikit-learn vs PyTorch Scikit-learn vs Embeddable
Looker
Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.

Compare Looker to PyTorch or Embeddable:

Looker vs PyTorch Looker vs Embeddable