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TFlearn VS PyCaret

Compare TFlearn VS PyCaret 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.

PyCaret logo PyCaret

open source, low-code machine learning library in Python
Not present
  • PyCaret Landing page
    Landing page //
    2022-03-19

TFlearn videos

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

PyCaret videos

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Quick tour of PyCaret (a low-code machine learning library in Python)

More videos:

  • Review - Automate Anomaly Detection Using Pycaret -Data Science And Machine Learning
  • Review - Machine Learning in Power BI with PyCaret- Podcast With Moez- Author Of Pycaret

Category Popularity

0-100% (relative to TFlearn and PyCaret)

TFlearn

PyCaret

OCR
100 100%
OCR
0% 0
Data Science And Machine Learning
62 62%
Data Science And Machine Learning
38% 38
Data Science Tools
0 0%
Data Science Tools
100% 100
Machine Learning
64 64%
Machine Learning
36% 36

User comments

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

PyCaret might be a bit more popular than TFlearn. We know about 2 links to it since March 2021 and only 2 links to TFlearn. 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 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 3 years ago

PyCaret mentions (2)

  • How to know what algorithm to apply? THEORY
    Anyway, nowadays there are autoML python packages that once you defined what type of problem you have to solve (e.g. regression, classification) , they automatically train differnt models at once and calculate the best performance. I used a lot the library Pycaret . Source: almost 2 years ago
  • 👌 Zero feature engineering with Upgini+PyCaret
    PyCaret - Low-code machine learning library in Python that automates machine learning workflows. Source: almost 2 years ago

What are some alternatives?

When comparing TFlearn and PyCaret, 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.

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

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.

Clarifai - The World's AI

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

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