Software Alternatives & Reviews

Kubeflow VS TFlearn

Compare Kubeflow VS TFlearn and see what are their differences

Kubeflow logo Kubeflow

Kubeflow makes deployment of ML Workflows on Kubernetes straightforward and automated

TFlearn logo TFlearn

TFlearn is a modular and transparent deep learning library built on top of Tensorflow.
  • Kubeflow Landing page
    Landing page //
    2023-10-11
Not present

Kubeflow videos

Kubeflow 0.6 Release Feature Review

More videos:

  • Review - Kubeflow @ApacheSpark Operator PR update with review feedback
  • Review - Sentiment Analysis using Kubernetes and Kubeflow

TFlearn videos

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

Category Popularity

0-100% (relative to Kubeflow and TFlearn)
Data Science And Machine Learning
OCR
0 0%
100% 100
Machine Learning Tools
100 100%
0% 0
Web Frameworks
100 100%
0% 0

User comments

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Social recommendations and mentions

TFlearn might be a bit more popular than Kubeflow. We know about 2 links to it since March 2021 and only 2 links to Kubeflow. 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.

Kubeflow mentions (2)

  • The Bacalhau Vision – A Distributed Compute over Data Platform
    I'm David Aronchick - first non-founding PM on Kubernetes, co-founder of Kubeflow [1], and co-founder of the SAME project [2] - and we've spent the past year working on Bacalhau [3], an open source project to bring compute to data. We've recently opened up a public-hosted cluster (all runnable from colab in our docs [4]) and would love your feedback - you can see our vision at the attached blog post. Thanks!... - Source: Hacker News / about 1 year ago
  • An update on relationships between stocks - STATISTICS ROCKS! - Brought to you by the SuperstonkQuants 🦍🥼🔬🚀
    You have GitHub org and a Vue based website up and running already, so it seems like you have tech logistics covered. Just in case it's useful, I have experience with Kubernetes, which can help run computationally intense workloads (even if GPUs are needed) or provide a pool of compute for something like Kubeflow (kubeflow.org). Here if you want, feel free to ignore if you're all covered in this area - I'll be... Source: almost 3 years ago

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 Kubeflow and TFlearn, you can also consider the following products

TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.

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

PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...

Clarifai - The World's AI

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.

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