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TFlearn VS Torch AI

Compare TFlearn VS Torch AI and see what are their differences

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TFlearn logo TFlearn

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

Torch AI logo Torch AI

Torch is a scientific computing framework for LuaJIT.
Not present
  • Torch AI Landing page
    Landing page //
    2019-09-21

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.

Torch AI features and specs

No features have been listed yet.

TFlearn videos

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

Torch AI videos

No Torch AI videos yet. You could help us improve this page by suggesting one.

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Category Popularity

0-100% (relative to TFlearn and Torch AI)

TFlearn

Torch AI

Data Science And Machine Learning
73 73%
Data Science And Machine Learning
27% 27
OCR
100 100%
OCR
0% 0
Data Science Tools
0 0%
Data Science Tools
100% 100
Data Dashboard
100 100%
Data Dashboard
0% 0

User comments

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Social recommendations and mentions

Based on our record, Torch AI 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 / almost 3 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

Torch AI mentions (3)

  • About luarocks, Lua ecosystem, etc.
    Here is the url to Torch: http://torch.ch/. Source: about 2 years ago
  • #
    I think you can use torch7 to do data science things but its development is a bit halted or something like that. It was pretty cool tho, you would have a C-level fast interpreter (LuaJIT) using a nice library. Source: over 3 years ago
  • iNeural : Update (8.12.21)
    It is developed by taking inspiration from libraries such as iNeural, FANN, pylearn2, EBLearn, Torch7. Written mostly in C++, iNeural also leverages the power of Python. The biggest reason for its development is that it needs very few dependencies. For this reason, it is expected to be suitable for working in systems with limited system requirements. - Source: dev.to / over 3 years ago

What are some alternatives?

When comparing TFlearn and Torch AI, 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.

Pylearn2 - Pylearn2 is a library for machine learning research.

Clarifai - The World's AI

Caffe - Caffe is an open source, deep learning framework.

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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