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Knet VS TFlearn

Compare Knet VS TFlearn and see what are their differences

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Knet logo Knet

Knet is a deep learning framework that supports GPU operation and automatic differentiation using dynamic computational graphs for models.

TFlearn logo TFlearn

TFlearn is a modular and transparent deep learning library built on top of Tensorflow.
  • Knet Landing page
    Landing page //
    2021-10-10
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Knet videos

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Play Doh Knetfiguren | deutsch - formen mit Knetix Knet-Set | Review and Fun

More videos:

  • Review - Review/Test: Soft-Knet-Set aus dem Müller Drogeriemarkt
  • Review - knet Mario review

TFlearn videos

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

Category Popularity

0-100% (relative to Knet and TFlearn)

Knet

TFlearn

OCR
38 38%
OCR
62% 62
Data Science And Machine Learning
38 38%
Data Science And Machine Learning
62% 62
Machine Learning
40 40%
Machine Learning
60% 60
Data Dashboard
36 36%
Data Dashboard
64% 64

User comments

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

Based on our record, TFlearn seems to be more popular. It has been mentiond 2 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.

Knet mentions (0)

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

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 1 year 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 3 years ago

What are some alternatives?

When comparing Knet and TFlearn, 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.

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.

Clarifai - The World's AI

Microsoft Cognitive Toolkit (Formerly CNTK) - Machine Learning

Merlin - Merlin is a deep learning framework written in Julia, it aims to provide a fast, flexible and compact deep learning library for machine learning.

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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