Software Alternatives & Reviews
Register | Login
RC

R Caret VS TFlearn

Compare R Caret VS TFlearn and see what are their differences

SafeBet.ai
Daily AI sports picks generated by artificial intelligence. SafeBet.ai helps you analyze all NBA, NFL, MLB, UFC and soccer games. It has a massive database by having analyzed all the games in the past 3 years. Use AI to improve your sports bets. featured
Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

R Caret logo R Caret

Documentation for the caret package.

TFlearn logo TFlearn

TFlearn is a modular and transparent deep learning library built on top of Tensorflow.
Not present
Not present

R Caret videos

No R Caret videos yet. You could help us improve this page by suggesting one.

+ Add video

TFlearn videos

+ Add

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

Category Popularity

0-100% (relative to R Caret and TFlearn)

R Caret

TFlearn

Data Science And Machine Learning
45 45%
Data Science And Machine Learning
55% 55
OCR
0 0%
OCR
100% 100
AI
100 100%
AI
0% 0
Machine Learning
45 45%
Machine Learning
55% 55

User comments

Share your experience with using R Caret and TFlearn. For example, how are they different and which one is better?
Log in or Post with

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.

R Caret mentions (0)

We have not tracked any mentions of R Caret yet. Tracking of R Caret 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 / over 1 year 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 R Caret and TFlearn, you can also consider the following products

H2O.ai - Democratizing Generative AI. Own your models: generative and predictive. We bring both super powers together with h2oGPT.

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

R MLstudio - The ML Studio is interactive for EDA, statistical modeling and machine learning applications.

Clarifai - The World's AI

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

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.

Loading...