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TFlearn VS PyTorch Lightning

Compare TFlearn VS PyTorch Lightning and see what are their differences

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Contents:
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  2. » Videos
  3. » Reviews
  4. » Alternatives

TFlearn logo TFlearn

TFlearn is a modular and transparent deep learning library built on top of Tensorflow.

PyTorch Lightning logo PyTorch Lightning

The light PyTorch wrapper for high-performance AI research
Not present
  • PyTorch Lightning Landing page
    Landing page //
    2023-04-21

TFlearn features and specs

  • User-Friendly Interface
    TFlearn provides a higher-level API that simplifies the process of building and training deep learning models, making it easier for beginners to use TensorFlow.
  • Modular Design
    It offers modular abstraction layers, allowing users to construct neural networks using pre-defined blocks which are easy to stack and customize.
  • Integration with TensorFlow
    TFlearn is built on top of TensorFlow, providing the flexibility and performance benefits of TensorFlow while enhancing its usability.
  • Pre-built Models
    It includes a range of pre-built models and algorithms for common machine learning tasks like classification and regression, facilitating quick experimentation.

Possible disadvantages of TFlearn

  • Lack of Updates
    TFlearn has not been actively maintained or updated in recent years, which may lead to compatibility issues with the latest versions of TensorFlow.
  • Limited Flexibility
    While TFlearn offers a simplified API, it may not offer the same level of customization and flexibility as using TensorFlow's core API directly.
  • Smaller Community
    As a niche library, TFlearn has a smaller user community, which could result in less community support and fewer resources compared to more popular libraries like Keras.
  • Performance Limitations
    Though built on top of TensorFlow, the added abstraction layers in TFlearn could potentially lead to minor performance overhead compared to pure TensorFlow implementations.

PyTorch Lightning features and specs

No features have been listed yet.

TFlearn videos

+ Add

Face Recognition using Deep Learning | Convolutional-Neural-Network | TensorFlow | TfLearn

PyTorch Lightning videos

+ Add

PYTORCH LIGHTNING COPYING FASTAI? 📰 DEEP NEWS 📰

More videos:

  • Review - vision transformer and Deit using PyTorch Lightning
  • Review - PyTorch Lightning Community Talks - Episode 3

Category Popularity

0-100% (relative to TFlearn and PyTorch Lightning)

TFlearn

PyTorch Lightning

Data Science And Machine Learning
79 79%
Data Science And Machine Learning
21% 21
Developer Tools
0 0%
Developer Tools
100% 100
OCR
100 100%
OCR
0% 0
AI
0 0%
AI
100% 100

User comments

Share your experience with using TFlearn and PyTorch Lightning. For example, how are they different and which one is better?
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Social recommendations and mentions

Based on our record, PyTorch Lightning should be more popular than TFlearn. It has been mentiond 3 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.

TFlearn mentions (2)

  • Beginner Friendly Resources to Master Artificial Intelligence and Machine Learning with Python (2022)
    TFLearn – Deep learning library featuring a higher-level API for TensorFlow. - Source: dev.to / over 2 years ago
  • Base ball
    Both the teams in a game are given their individual ID values and are made into vectors. Relevant data like the home and away team, home runs, RBI’s, and walk’s are all taken into account and passed through layers. There’s no need to reinvent the wheel here, there's a multitude of libraries that enable a coder to implement machine learning theories efficiently. In this case we will be using a library called... - Source: dev.to / about 4 years ago

PyTorch Lightning mentions (3)

  • SB-1047 will stifle open-source AI and decrease safety
    It's very easy to get started, right in your Terminal, no fees! No credit card at all. And there are cloud providers like https://replicate.com/ that will let you use your LLM via an API key just like you did with OpenAI if you need that. You don't need OpenAI - nobody does. - Source: Hacker News / about 1 year ago
  • Como empezar con inteligencia artificial?
    Https://see.stanford.edu/Course/CS229 Https://lightning.ai/ Https://www.youtube.com/watch?v=00s9ireCnCw&t=57s Https://towardsdatascience.com/. Source: over 1 year ago
  • [D] What Repetitive Tasks Related to Machine Learning do You Hate Doing?
    There is already a ton of momentum around automating ML workflows. I would suggest you contribute to a preexisting project like, for instance, PyTorch Lightning or fast.ai. Source: about 3 years ago

What are some alternatives?

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

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

Facebook.ai - Everything you need to take AI from research to production

Clarifai - The World's AI

Swift AI - Artificial intelligence and machine learning library written in Swift.

DeepPy - DeepPy is a MIT licensed deep learning framework that tries to add a touch of zen to deep learning as it allows for Pythonic programming.

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.

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