quickai VS segyio

Compare quickai vs segyio and see what are their differences.

quickai

QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models. (by geekjr)

segyio

Fast Python library for SEGY files. (by equinor)
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quickai segyio
7 1
162 461
- 0.7%
3.7 5.6
30 days ago 5 months ago
Python Python
MIT License GNU General Public License v3.0 or later
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

quickai

Posts with mentions or reviews of quickai. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-05-05.

segyio

Posts with mentions or reviews of segyio. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing quickai and segyio you can also consider the following projects:

detoxify - Trained models & code to predict toxic comments on all 3 Jigsaw Toxic Comment Challenges. Built using ⚡ Pytorch Lightning and 🤗 Transformers. For access to our API, please email us at [email protected].

Lenia - Lenia - Mathematical Life Forms

gpt-neo_dungeon - Colab notebooks to run a basic AI Dungeon clone using gpt-neo-2.7B

bottleneck - Fast NumPy array functions written in C

YOLOv6 - YOLOv6: a single-stage object detection framework dedicated to industrial applications.

ME-PHYS_Undergraduate_Courses - Here will be some of the codes I used whilst studying Mechanical Engineering and Physics at the Bilkent University.

chappie.ai - Generalized AI to perform a multitude of tasks written in python3

Note - Easily implement parallel training and distributed training. Machine learning library. Note.neuralnetwork.tf package include Llama2, Llama3, CLIP, ViT, ConvNeXt, SwiftFormer, etc, these models built with Note are compatible with TensorFlow and can be trained with TensorFlow.

happy-transformer - Happy Transformer makes it easy to fine-tune and perform inference with NLP Transformer models.

TabFormer - Code & Data for "Tabular Transformers for Modeling Multivariate Time Series" (ICASSP, 2021)

TensorLayer - Deep Learning and Reinforcement Learning Library for Scientists and Engineers

rtdl - Research on Tabular Deep Learning [Moved to: https://github.com/yandex-research/rtdl]