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RailModeller VS TFlearn

Compare RailModeller VS TFlearn and see what are their differences

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RailModeller logo RailModeller

RailModeller is a new application for creating model railroad and slot car layouts.

TFlearn logo TFlearn

TFlearn is a modular and transparent deep learning library built on top of Tensorflow.
  • RailModeller Landing page
    Landing page //
    2021-07-23
Not present

RailModeller videos

+ Add

RailModeller Pro Tutorial: Getting started (english)

More videos:

  • Tutorial - How To Build A Model Railway - Episode 4 - How to design & plan | RailModeller Pro
  • Review - Introducing RailModeller Pro

TFlearn videos

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

Category Popularity

0-100% (relative to RailModeller and TFlearn)

RailModeller

TFlearn

Architecture
100 100%
Architecture
0% 0
OCR
0 0%
OCR
100% 100
CRM
100 100%
CRM
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100

User comments

Share your experience with using RailModeller 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.

RailModeller mentions (0)

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

SCARM - Simple Computer Aided Railway Modeller

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

TrainCad - Freeware Microsoft Windows program for designing model railroad layouts using standard tracks.

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.

AnyRail - AnyRail makes model railroad design so easy, it's fun!

Clarifai - The World's AI

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