Software Alternatives, Accelerators & Startups

Thinc VS Exploratory

Compare Thinc VS Exploratory and see what are their differences

Thinc logo Thinc

Thinc is a lightweight type-checked deep learning library for composing models, with support for layers defined in frameworks like PyTorch and TensorFlow.

Exploratory logo Exploratory

Exploratory enables users to understand data by transforming, visualizing, and applying advanced statistics and machine learning algorithms.
  • Thinc Landing page
    Landing page //
    2023-05-14
  • Exploratory Landing page
    Landing page //
    2023-09-12

Thinc videos

Best Practices for Fingerprint Enrolment Process on ThinC-AUTH Biometric Security Key

More videos:

  • Review - HOOMAN.. DON EVEN THINC ABOUT IT
  • Review - Review jujur : somethinc aha bha pha peeling solution the ordinary aha bha peeling solution

Exploratory videos

1.3 Exploratory, Descriptive and Explanatory Nature Of Research

More videos:

  • Review - Exploratory Process Content Review
  • Review - Reviewing Your Data Science Projects - Episode 1 (Exploratory Analysis)

Category Popularity

0-100% (relative to Thinc and Exploratory)
Data Science And Machine Learning
Machine Learning
100 100%
0% 0
Data Science Tools
0 0%
100% 100
AI
100 100%
0% 0

User comments

Share your experience with using Thinc and Exploratory. For example, how are they different and which one is better?
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Social recommendations and mentions

Based on our record, Exploratory should be more popular than Thinc. It has been mentiond 6 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.

Thinc mentions (1)

  • good examples of functional-like python code that one can study?
    Thinc - defining neural nets in functional way Jax, a new deep learning framework puts emphasis on functions rather than tensors, I've tested it for a couple of applications and it's really cool, you can write stuff like you'd write math expressions in papers using numpy. That speeds up development significantly, and makes code much more readable. Source: almost 3 years ago

Exploratory mentions (6)

  • Excel Never Dies
    I'm a happy customer of https://exploratory.io/ - it's a very user-friendly interface on top of R and I think you might find it helpful. - Source: Hacker News / almost 2 years ago
  • Fast Lane to Learning R
    If the goal here is becoming productive quickly, try https://exploratory.io/ which is a sort of WYSIWYG environment for R that will still let you code by hand if needed. No affiliation, just a happy customer for 2 years. - Source: Hacker News / about 2 years ago
  • Excel 2.0 – Is there a better visual data model than a grid of cells?
    Give https://exploratory.io/ a look. It's free/cheap. It's a nice easy GUI wrapper for R and just works. I stumbled across it a year ago and now use it daily. - Source: Hacker News / about 2 years ago
  • Why no love for Exploratory Desktop?
    I'm not associated with the company, but I have used their product extensively and recommended it before. Is there a reason people do not recommend Exploratory Desktop compared to something like Tableau? It is free for public use, and can do almost anything Tableau does but faster: https://exploratory.io/. Source: about 2 years ago
  • A Quick Introduction to R
    I've been using https://exploratory.io/ a lot, which is r in a really nice wrapper where you can do everything point and click, by writing code by hand or a mix. - Source: Hacker News / over 2 years ago
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What are some alternatives?

When comparing Thinc and Exploratory, you can also consider the following products

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

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

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.

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

OpenAI Gym - OpenAI GYM is a toolkit developers use to both develop and compare reinforcement learning algorithms. Their GitHub repository includes dozens of contributors... read more.