Deep Learning Visuals contains 215 unique images divided in 23 categories

Overview

Deep Learning Visuals

Shield: CC BY 4.0

This repository was inspired by the ML Visuals repository maintained by dair.ai.

Deep Learning Visuals contains 215 unique images divided in 23 categories (some images may appear in more than one category). All the images were originally published in my book "Deep Learning with PyTorch Step-by-Step: A Beginner's Guide".

Can I Freely Use These Images?

Sure, these images can be FREELY USED in your own blog posts, slides, presentations, or papers under the CC-BY license.

Awesome, where are they?

You can easily navigate through the pages and indices, and click on the desired image to visualize it in full size:

How Can I Use Them?

DISCLAIMER: this is NOT legal advice, you should always read the license yourself!

In a nutshell, you're allowed to use (or adapt) these images in your own materials, even for commercial purposes, as long as you attribute it.

Here is a quick guide on Best Practices for Attribution.

Here are some examples of both images and attributions:

Logistic Regression

Image by dvgodoy / CC BY

RNN

Image by dvgodoy / CC BY

Transformer

Image by dvgodoy / CC BY

This work is licensed under a Creative Commons Attribution 4.0 International License.

CC BY 4.0

Owner
Daniel Voigt Godoy
Data scientist, developer, teacher and writer. Author of "Deep Learning with PyTorch Step-by-Step: A Beginner's Guide".
Daniel Voigt Godoy
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Machine learning evaluation metrics, implemented in Python, R, Haskell, and MATLAB / Octave

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NeX: Real-time View Synthesis with Neural Basis Expansion Project Page | Video | Paper | COLAB | Shiny Dataset We present NeX, a new approach to novel

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NumPy로 구현한 딥러닝 라이브러리입니다. (자동 미분 지원)

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You can draw the corresponding bounding box into the image and save it according to the result file (txt format) run by the tracker.

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Huiyiqianli 42 Dec 06, 2022
[NeurIPS-2021] Mosaicking to Distill: Knowledge Distillation from Out-of-Domain Data

MosaicKD Code for NeurIPS-21 paper "Mosaicking to Distill: Knowledge Distillation from Out-of-Domain Data" 1. Motivation Natural images share common l

ZJU-VIPA 37 Nov 10, 2022
Code base of object detection

rmdet code base of object detection. 环境安装: 1. 安装conda python环境 - `conda create -n xxx python=3.7/3.8` - `conda activate xxx` 2. 运行脚本,自动安装pytorch1

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Controlling the MicriSpotAI robot from scratch

Abstract: The SpotMicroAI project is designed to be a low cost, easily built quadruped robot. The design is roughly based off of Boston Dynamics quadr

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thundernet ncnn

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Go from graph data to a secure and interactive visual graph app in 15 minutes. Batteries-included self-hosting of graph data apps with Streamlit, Graphistry, RAPIDS, and more!

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