LiDAR-Guide VS softlearning

Compare LiDAR-Guide vs softlearning and see what are their differences.

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LiDAR-Guide softlearning
1 4
57 1,157
- 1.6%
3.2 0.0
4 months ago 5 months ago
Python Python
- 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.

LiDAR-Guide

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

softlearning

Posts with mentions or reviews of softlearning. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-12-09.

What are some alternatives?

When comparing LiDAR-Guide and softlearning you can also consider the following projects:

VeloView - VeloView performs real-time visualization and easy processing of live captured 3D LiDAR data from Velodyne sensors (Alpha Prime™, Puck™, Ultra Puck™, Puck Hi-Res™, Alpha Puck™, Puck LITE™, HDL-32, HDL-64E). Runs on Windows, Linux and MacOS. This repository is a mirror of https://gitlab.kitware.com/LidarView/VeloView-Velodyne.

deep-RL-trading - playing idealized trading games with deep reinforcement learning

Photogrammetry-Guide - Photogrammetry Guide. Photogrammetry is widely used for Aerial surveying, Agriculture, Architecture, 3D Games, Robotics, Archaeology, Construction, Emergency management, and Medical.

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.

awesome-experimental-standards-deep-learning - Repository collecting resources and best practices to improve experimental rigour in deep learning research.

tmrl - Reinforcement Learning for real-time applications - host of the TrackMania Roborace League

Data-Engineering-Roadmap - Roadmap for Data Engineering

rl-baselines3-zoo - A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.

trax - Trax — Deep Learning with Clear Code and Speed

awesome-deep-trading - List of awesome resources for machine learning-based algorithmic trading

senza - Experiments with drone control and reinforcement learning.