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MLKit VS TFlearn

Compare MLKit VS TFlearn and see what are their differences

LibHunt
LibHunt tracks mentions of software libraries on relevant social networks. Based on that data, you can find the most popular projects and their alternatives. featured
Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

MLKit logo MLKit

MLKit is a simple machine learning framework written in Swift.

TFlearn logo TFlearn

TFlearn is a modular and transparent deep learning library built on top of Tensorflow.
  • MLKit Landing page
    Landing page //
    2023-09-15
Not present

MLKit videos

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Android Face Detection using Camera - Google MLKit Face Detection Android Studio - Firebase ML Kit

TFlearn videos

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

Category Popularity

0-100% (relative to MLKit and TFlearn)

MLKit

TFlearn

Data Science And Machine Learning
61 61%
Data Science And Machine Learning
39% 39
OCR
0 0%
OCR
100% 100
Data Science Tools
100 100%
Data Science Tools
0% 0
Python Tools
100 100%
Python Tools
0% 0

User comments

Share your experience with using MLKit 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.

MLKit mentions (0)

We have not tracked any mentions of MLKit yet. Tracking of MLKit 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 / 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

What are some alternatives?

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

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

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

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Clarifai - The World's AI

OpenCV - OpenCV is the world's biggest computer vision library

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.

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