Software Alternatives & Reviews

Tensor2Tensor VS Scikit-learn

Compare Tensor2Tensor VS Scikit-learn and see what are their differences

Tensor2Tensor logo Tensor2Tensor

Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research. - tensorflow/tensor2tensor

Scikit-learn logo Scikit-learn

scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
  • Tensor2Tensor Landing page
    Landing page //
    2023-09-11
  • Scikit-learn Landing page
    Landing page //
    2022-05-06

Tensor2Tensor

Categories
  • Application And Data
  • Application Utilities
  • Machine Learning Tools
  • Data Science And Machine Learning
  • Machine Learning
Website github.com
Details $-

Scikit-learn

Categories
  • Data Science And Machine Learning
  • Data Science Tools
  • Python Tools
  • Software Libraries
Website scikit-learn.org
Details $

Tensor2Tensor videos

Tensor2Tensor (TensorFlow @ O’Reilly AI Conference, San Francisco '18)

More videos:

  • Tutorial - How to Use Tensor2Tensor & Clusterone to Train Models on OpenSLR
  • Review - Machine Learning with Google Brain’s Tensor2Tensor

Scikit-learn videos

Learning Scikit-Learn (AI Adventures)

More videos:

  • Review - Python Machine Learning Review | Learn python for machine learning. Learn Scikit-learn.

Category Popularity

0-100% (relative to Tensor2Tensor and Scikit-learn)
Data Science And Machine Learning
Machine Learning Tools
100 100%
0% 0
Data Science Tools
0 0%
100% 100
Application And Data
100 100%
0% 0

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Reviews

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Scikit-learn Reviews

15 data science tools to consider using in 2021
Scikit-learn is an open source machine learning library for Python that's built on the SciPy and NumPy scientific computing libraries, plus Matplotlib for plotting data. It supports both supervised and unsupervised machine learning and includes numerous algorithms and models, called estimators in scikit-learn parlance. Additionally, it provides functionality for model...

Social recommendations and mentions

Based on our record, Scikit-learn seems to be more popular. It has been mentiond 27 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.

Tensor2Tensor mentions (0)

We have not tracked any mentions of Tensor2Tensor yet. Tracking of Tensor2Tensor recommendations started around Mar 2021.

Scikit-learn mentions (27)

  • Link Prediction With node2vec in Physics Collaboration Network
    Firstly, we need a connection to Memgraph so we can get edges, split them into two parts (train set and test set). For edge splitting, we will use scikit-learn. In order to make a connection towards Memgraph, we will use gqlalchemy. - Source: dev.to / 10 months ago
  • WiFilter is a RaspAP install extended with a squidGuard proxy to filter adult content. Great solution for a family, schools and/or public access point
    The ML component is based on scikit-learn which differentiates it from purely list-based filters. It couples this with a full-featured wireless router (RaspAP) in a single device, so it fulfills the needs of a use case not entirely addressed by Pi-hole. Source: 11 months ago
  • PSA: You don't need fancy stuff to do good work.
    Finally, when it comes to building models and making predictions, Python and R have a plethora of options available. Libraries like scikit-learn, statsmodels, and TensorFlowin Python, or caret, randomForest, and xgboostin R, provide powerful machine learning algorithms and statistical models that can be applied to a wide range of problems. What's more, these libraries are open-source and have extensive... Source: 12 months ago
  • Help on using R for Machine Learning?
    Scikit-learn is a machine learning library that comes with a number of pre-built machine learning models, which can then be used as python wrappers. Source: about 1 year ago
  • Machine learning with Julia - Solve Titanic competition on Kaggle and deploy trained AI model as a web service
    This is not a book, but only an article. That is why it can't cover everything and assumes that you already have some base knowledge to get the most from reading it. It is essential that you are familiar with Python machine learning and understand how to train machine learning models using Numpy, Pandas, SciKit-Learn and Matplotlib Python libraries. Also, I assume that you are familiar with machine learning... - Source: dev.to / about 1 year ago
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What are some alternatives?

When comparing Tensor2Tensor and Scikit-learn, you can also consider the following products

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

OpenCV - OpenCV is the world's biggest computer vision library

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.

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

CUDA - Select Target Platform Click on the green buttons that describe your target platform.

NumPy - NumPy is the fundamental package for scientific computing with Python