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Covidence VS TFlearn

Compare Covidence VS TFlearn and see what are their differences

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

Covidence logo Covidence

The world's leading software for managing and streamlining your systematic review. Discover how to do a systematic review in less time, while maintaining quality and accuracy.

TFlearn logo TFlearn

TFlearn is a modular and transparent deep learning library built on top of Tensorflow.
  • Covidence Landing page
    Landing page //
    2021-09-27
Not present

Covidence videos

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Using Covidence for Conducting Systematic Reviews

More videos:

  • Review - Covidence: Accelerate Your Systematic Review
  • Demo - Covidence Demo

TFlearn videos

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

Category Popularity

0-100% (relative to Covidence and TFlearn)

Covidence

TFlearn

Food And Beverage
100 100%
Food And Beverage
0% 0
OCR
0 0%
OCR
100% 100
Systematic Reviews
100 100%
Systematic Reviews
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100

User comments

Share your experience with using Covidence 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.

Covidence mentions (0)

We have not tracked any mentions of Covidence yet. Tracking of Covidence recommendations started around Jun 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 Covidence and TFlearn, you can also consider the following products

Distiller - Distiller's hosted continuous integration platform takes the pain out of mobile development through automated build, test, and deployment of your iOS apps.

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

DistillerSR by Evidence Partners - DistillerSR automates every stage of your literature reviews to produce evidence-based research faster and more accurately.

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.

Drammer Whisky App - User friendly app to track & share your whisky experiences 🥃

Clarifai - The World's AI

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