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Upsource VS TFlearn

Compare Upsource VS TFlearn and see what are their differences

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Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Upsource logo Upsource

Upsource provides unified access to all your projects stored in Git, Perforce, Mercurial or Subversion.

TFlearn logo TFlearn

TFlearn is a modular and transparent deep learning library built on top of Tensorflow.
  • Upsource Landing page
    Landing page //
    2023-04-27
Not present

Upsource videos

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Upsource Overview

More videos:

  • Review - Code review workflow in Upsource
  • Review - Introducing JetBrains Upsource: Repository browser and code review tool

TFlearn videos

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

Category Popularity

0-100% (relative to Upsource and TFlearn)

Upsource

TFlearn

Code Collaboration
100 100%
Code Collaboration
0% 0
OCR
0 0%
OCR
100% 100
Git
100 100%
Git
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100

User comments

Share your experience with using Upsource 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.

Upsource mentions (0)

We have not tracked any mentions of Upsource yet. Tracking of Upsource 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 Upsource and TFlearn, you can also consider the following products

BitBucket - Bitbucket is a free code hosting site for Mercurial and Git. Manage your development with a hosted wiki, issue tracker and source code.

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

Phabricator - Phacility - Phabricator

Clarifai - The World's AI

GitHub - Originally founded as a project to simplify sharing code, GitHub has grown into an application used by over a million people to store over two million code repositories, making GitHub the largest code host in the world.

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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