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https://github.com/generalistcodes/awesomeai

Curated list of Awesome AI Apps and Projects(Open Source and Non Open Source)
https://github.com/generalistcodes/awesomeai
List: awesomeai
Last synced: 16 days ago
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Curated list of Awesome AI Apps and Projects(Open Source and Non Open Source)
Host: GitHub
URL: https://github.com/generalistcodes/awesomeai
Owner: generalistcodes
Created: 2022-12-04T15:43:41.000Z (about 2 years ago)
Default Branch: main
Last Pushed: 2022-12-04T15:45:54.000Z (about 2 years ago)
Last Synced: 2024-05-27T21:21:01.416Z (7 months ago)
Size: 6.84 KB
Stars: 3
Watchers: 1
Forks: 0
Open Issues: 0
Metadata Files:
- Readme: README.md
Awesome Lists containing this project

ultimate-awesome - awesomeai - Curated list of Awesome AI Apps and Projects(Open Source and Non Open Source). (Other Lists / PowerShell Lists)
README

        # Awesome AI

Curated list of Awesome AI Apps and Projects(Open Source and Non Open Source)

If you want to contribute to this list (please do), send me a pull request.

# Table of Contents

- [Artificial Intelligence(AI)](#AI)

- [Machine Learning(ML)](#ML)

- [Deep Learning(DL)](#DL)

- [Computer Vision(CV)](#CV)

- [Natural Language Processing(NLP)](#NLP)

- [Speech Recognition](#SR)

- [Other Research Topics](#ORT)

- [Programming Languages](#PL)

- [Framework](#Framework)

- [Datasets](#Datasets)

- [AI Career](#AI Career)



# Artificial Intelligence(AI)

- [AI](https://github.com/owainlewis/awesome-artificial-intelligence)

- [AI-Use-Cases](https://github.com/faktionai/awesome-ai-usecases)

- [AI residency programs information](https://github.com/ankitshah009/all-about-ai-residency)

- [Explainable AI](https://github.com/wangyongjie-ntu/Awesome-explainable-AI)



# Machine Learning(ML)

- [ML](https://github.com/josephmisiti/awesome-machine-learning)

- [ML-Source-Code](https://github.com/src-d/awesome-machine-learning-on-source-code)

- [ML-CN](https://github.com/jobbole/awesome-machine-learning-cn)

- [Adversarial-ML](https://github.com/yenchenlin/awesome-adversarial-machine-learning)

- [Quantum-ML](https://github.com/krishnakumarsekar/awesome-quantum-machine-learning)

- [3D-Machine-Learning](https://github.com/timzhang642/3D-Machine-Learning)

- [Machine Learning Interpretability](https://github.com/jphall663/awesome-machine-learning-interpretability)

- [Machine Learning System](https://github.com/HuaizhengZhang/Awesome-System-for-Machine-Learning)

- [Mobile Machine Learning](https://github.com/fritzlabs/Awesome-Mobile-Machine-Learning)

- [Machine Learning Problems](https://github.com/RedditSota/state-of-the-art-result-for-machine-learning-problems)

- [Gradient Boosting](https://github.com/benedekrozemberczki/awesome-gradient-boosting-papers)

- [Decision Tree](https://github.com/benedekrozemberczki/awesome-decision-tree-papers)



# Deep Learning(DL)

- [DL](https://github.com/ChristosChristofidis/awesome-deep-learning)

- [DL-Papers](https://github.com/terryum/awesome-deep-learning-papers)

- [DL-Resources](https://github.com/guillaume-chevalier/Awesome-Deep-Learning-Resources)

- [DeepLearning-500-questions](https://github.com/scutan90/DeepLearning-500-questions)

- [Deep-Learning-in-Production](https://github.com/ahkarami/Deep-Learning-in-Production)

- [DNN Compression and Acceleration](https://github.com/MingSun-Tse/EfficientDNNs)

- [Architecture Search](https://github.com/markdtw/awesome-architecture-search)

- [Deep Learning for Graphs](https://github.com/DeepGraphLearning/LiteratureDL4Graph)

- [Real-time Network](https://github.com/wpf535236337/real-time-network)

- [Deep Learning Interpretability](https://github.com/oneTaken/awesome_deep_learning_interpretability)

- [Graph-based Deep Learning](https://github.com/naganandy/graph-based-deep-learning-literature)



# Computer Vision(CV)

- [CV](https://github.com/jbhuang0604/awesome-computer-vision)

- [CV2](https://github.com/kjw0612/awesome-deep-vision)

- [CV-People](Awesome-People-in-Computer-Vision)

- [DeepFakes](https://github.com/datamllab/awesome-deepfakes-materials)

- [Event-based Vision Resources](https://github.com/uzh-rpg/event-based_vision_resources)

- [Embodied Vision](https://github.com/ChanganVR/awesome-embodied-vision)

- Research Topics

    - [Action Recognition](https://github.com/jinwchoi/awesome-action-recognition)

    - [Colorization](https://github.com/MarkMoHR/Awesome-Image-Colorization)

    - [Image Classification](https://github.com/weiaicunzai/awesome-image-classification)

        - [imgclsmob](https://github.com/osmr/imgclsmob)

    - [Image Registration](https://github.com/Awesome-Image-Registration-Organization/awesome-image-registration)

    - Object Detection

        - [amusi/Object Detection](https://github.com/amusi/awesome-object-detection)

        - [hoya012/Object Detection]( https://github.com/hoya012/deep_learning_object_detection )

        - [Tiny Object Detection](https://github.com/kuanhungchen/awesome-tiny-object-detection)

        - [Small Object Detection](https://github.com/tjtum-chenlab/SmallObjectDetectionList)

        - [Video Object Detection](https://github.com/huanglianghua/video-detection-paper-list)

        - [Anchor Free Object Detection](https://github.com/XinZhangNLPR/awesome-anchor-free-object-detection)

    - Face

        - [Face Detection & Recognition](https://github.com/ChanChiChoi/awesome-Face_Recognition)

        - [awesome-face](https://github.com/polarisZhao/awesome-face)

        - [Facial Expression Recognition (FER)](https://github.com/EvelynFan/AWESOME-FER)

        - [Face Landmark Detection](https://github.com/mrgloom/Face-landmarks-detection-benchmark)

        - [Landmark Detection](https://github.com/D-X-Y/landmark-detection)

        - [Face Anti-spoofing](https://github.com/ZitongYu/DeepFAS)

    - [Gaze Estimation](https://github.com/WuZhuoran/awesome-gaze)

    - [HDR Image Synthesis](https://github.com/vinthony/awesome-deep-hdr)

    - Image Segmentation

        - [Semantic Segmentation](https://github.com/mrgloom/awesome-semantic-segmentation)

        - [Segmentation.X](https://github.com/wutianyiRosun/Segmentation.X)

        - [Panoptic Segmentation](https://github.com/Angzz/awesome-panoptic-segmentation)

        - [Weakly Supervised Semantic Segmentation](https://github.com/YimingCuiCuiCui/awesome-weakly-supervised-segmentation)

        - [Referring Image Segmentation](https://github.com/MarkMoHR/Awesome-Referring-Image-Segmentation)

        - [Semi Supervised Learning for Medical Image Segmentation](https://github.com/HiLab-git/SSL4MIS)

    - [Object Tracking](https://github.com/foolwood/benchmark_results)

        - [Visual Tracking1](https://github.com/foolwood/benchmark_results)

        - [Visual Tracking2](https://github.com/czla/daily-paper-visual-tracking)

        - [Multi-Object Tracking](https://github.com/SpyderXu/multi-object-tracking-paper-list)

        - [Tracking and Detection](https://github.com/abhineet123/Deep-Learning-for-Tracking-and-Detection)

        - [daily-paper-visual-tracking](https://github.com/czla/daily-paper-visual-tracking)

        - [Multimodal Tracking](https://github.com/zhang-pengyu/Multimodal-Tracking-Survey)

    - [Pose estimation](https://github.com/wjbKimberly/pose_estimation_CVPR_ECCV_2018)

        - [Object Pose Estimation](https://github.com/YoungXIAO13/ObjectPoseEstimationSummary)

        - Human Pose estimation

          - [Human Pose estimation 1](https://github.com/cbsudux/awesome-human-pose-estimation)

          - [Human Pose estimation 2](https://github.com/wangzheallen/awesome-human-pose-estimation)

        - [Hand Pose estimation](https://github.com/xinghaochen/awesome-hand-pose-estimation)

        - [6D Object Pose Estimation](https://github.com/ZhongqunZHANG/awesome-6d-object)

    - [Human Motion](https://github.com/derikon/awesome-human-motion)

    - [Human-Object Interaction(HOI)](https://github.com/DirtyHarryLYL/HOI-Learning-List)

    - [Long-tailed](https://github.com/zwzhang121/Awesome-of-Long-Tailed-Recognition)

    - Scene Text

        - [Scene Text Localization and Recognition](https://github.com/chongyangtao/Awesome-Scene-Text-Recognition)

        - [Scene Text Localization & Recognition Resources](https://github.com/whitelok/image-text-localization-recognition)

        - [Scene Text Detection and Recognition](https://github.com/Jyouhou/SceneTextPapers)

        - [Text Detection and Recognition](https://github.com/hwalsuklee/awesome-deep-text-detection-recognition)

        - [Scene Text Recognition Resources](https://github.com/HCIILAB/Scene-Text-Recognition)

    - Super Resolution

        - [Super Resolution (ChaofWang)](https://github.com/ChaofWang/Awesome-Super-Resolution)

        - [Super Resolution (ptkin)]()

        - [Image Super Resolution](https://github.com/YapengTian/Single-Image-Super-Resolution)

        - [Video Super Resolution](https://github.com/LoSealL/VideoSuperResolution)

    - 3D

        - [3D Reconstruction](https://github.com/openMVG/awesome_3DReconstruction_list)

        - [3D Human Body](https://github.com/3DFaceBody/awesome-3dbody-papers)

    - [OCR](https://github.com/kba/awesome-ocr)

    - Re-ID

        - [Person Re-ID(1)](https://github.com/bismex/Awesome-person-re-identification)

        - [Person Re-ID(2)](https://github.com/FDU-VTS/Awesome-Person-Re-Identification)

        - [Vehicle Re-ID(1)](https://github.com/layumi/Vehicle_reID-Collection)

        - [Vehicle Re-ID(2)](https://github.com/knwng/awesome-vehicle-re-identification)

    - [Pedestrian Attribute Recognition](https://github.com/wangxiao5791509/Pedestrian-Attribute-Recognition-Paper-List)

    - [Person Search](https://github.com/wangxiao5791509/Person-Search-Paper-List)

    - [Image Captioning](https://github.com/zhjohnchan/awesome-image-captioning)

    - [Question Answering](https://github.com/dapurv5/awesome-question-answering)

    - [Crowd Counting](https://github.com/gjy3035/Awesome-Crowd-Counting)

    - [Lane Detection](https://github.com/amusi/awesome-lane-detection)

    - [Low Lignt Enhancement](https://github.com/Elin24/Awesome-Low-Lignt-Enhancement) 

    - Image Retrieval

        - [Awesome image retrieval papers (1)](https://github.com/willard-yuan/awesome-cbir-papers)

        - [Awesome image retrieval papers (2)](https://github.com/lgbwust/awesome-image-retrieval-papers)

    - [Medical Imaging](https://github.com/fepegar/awesome-medical-imaging)

        - [Medical Data](https://github.com/beamandrew/medical-data)

        - [Medical imaging datasets](https://github.com/sfikas/medical-imaging-datasets)

        - [Awesome GAN for Medical Imaging](https://github.com/xinario/awesome-gan-for-medical-imaging)

        - [Deep Learning for Medical Applications](https://github.com/albarqouni/Deep-Learning-for-Medical-Applications)

        - [Medical Image Segmentation](https://github.com/JunMa11/SOTA-MedSeg) 

    - [Image Inpainting](https://github.com/1900zyh/Awesome-Image-Inpainting)

    - Image/Video Dehazing

        - [awesome-dehazing](https://github.com/youngguncho/awesome-dehazing)

        - [DehazeZoo](https://github.com/cxtalk/DehazeZoo)

    - Image Denoising

        - [reproducible-image-denoising-state-of-the-art](https://github.com/wenbihan/reproducible-image-denoising-state-of-the-art)

        - [Image-Denoising-State-of-the-art](https://github.com/flyywh/Image-Denoising-State-of-the-art)

        - [Image and Video Denoising](https://github.com/z-bingo/awesome-image-denoising-state-of-the-art)

        - [Awesome-Denoise](https://github.com/oneTaken/Awesome-Denoise)

    - [Image Deraining](https://github.com/nnUyi/DerainZoo)

    - [Image/Video Deblurring]( https://github.com/subeeshvasu/Awesome-Deblurring )

    - Image to Image(img2img)

        - [lzhbrian/Image to Image](https://github.com/lzhbrian/image-to-image-papers)

        - [xiaweihao/Image to Image](https://github.com/xiaweihao/awesome-image-translation)

    - [Multi-View Stereo(MVS)](https://github.com/XYZ-qiyh/Awesome-Learning-MVS)

    - [Underwater Image Enhancement](https://github.com/cxtalk/Awesome-Underwater-Image-Enhancement)

    - [Video Analysis](https://github.com/HuaizhengZhang/Awsome-Deep-Learning-for-Video-Analysis)

    - [Video Object Segmentation(VOS)](https://github.com/du0915/Video-Object-Segmentation-Paper-List)

    - [Edge Detection]()

    - [Local and Global Descriptor](https://github.com/shamangary/awesome-local-global-descriptor)

    - [Referring Image Segmentation](https://github.com/MarkMoHR/Awesome-Referring-Image-Segmentation)

    - Salience

        - [Salient Object Detection(SOD)](https://github.com/jiwei0921/SOD-CNNs-based-code-summary-)

        - [Saliency Detection & Segmentation](https://github.com/lartpang/awesome-segmentation-saliency-dataset#another-awesome-dataset-list)

        - [RGB-D Salient Object Detection](https://github.com/taozh2017/RGBD-SODsurvey)

    - [Self-Supervised Learning in Medical Imaging](https://github.com/SaeedShurrab/awesome-self-supervised-learning-in-medical-imaging)

    - [Fashion + AI](https://github.com/lzhbrian/Cool-Fashion-Papers)

    - [Event-based Vision Resources](https://github.com/uzh-rpg/event-based_vision_resources)

    - [Video Stabilization](https://github.com/yaochih/awesome-video-stabilization)

    - Visual Transformer

        - [Transformer-in-Vision](https://github.com/DirtyHarryLYL/Transformer-in-Vision)

        - [Awesome Transformer for Vision Resources List](https://github.com/lijiaman/awesome-transformer-for-vision)

        - [Awesome-Visual-Transformer](https://github.com/dk-liang/Awesome-Visual-Transformer)

        - [Awesome Visual Representation Learning with Transformers](https://github.com/alohays/awesome-visual-representation-learning-with-transformers)



# Natural Language Processing(NLP)

- [NLP](https://github.com/keon/awesome-nlp)

- [NLP-progress](https://github.com/sebastianruder/NLP-progress)

- [CoreNLP](https://github.com/stanfordnlp/CoreNLP)

- [NLPIR](https://github.com/NLPIR-team/NLPIR)

- [nlp_course](https://github.com/yandexdataschool/nlp_course)

- [nlp-datasets](https://github.com/niderhoff/nlp-datasets)

- [nlp-reading-group](https://github.com/clulab/nlp-reading-group)

- [NLP Paper](https://github.com/changwookjun/nlp-paper)

- [Awesome-Chinese-NLP](https://github.com/crownpku/Awesome-Chinese-NLP): 中文自然语言处理相关资料

- [awesome-dl4nlp](https://github.com/brianspiering/awesome-dl4nlp)

- [awesome-sentence-embedding](https://github.com/Separius/awesome-sentence-embedding)

- Research Topics

  - [Machine Translation](https://github.com/ZNLP/SOTA-MT) 



# Speech Recognition

- [speech_recognition](https://github.com/Uberi/speech_recognition)

- [awesome-speech-recognition-speech-synthesis-papers](https://github.com/zzw922cn/awesome-speech-recognition-speech-synthesis-papers)



# Other Research Topics

- Bayesian

     - [Bayesian](https://github.com/dimenwarper/awesome-bayes)

     - [Deep Bayesian](https://github.com/otokonoko8/deep-Bayesian-nonparametrics-papers)

- [Capsule Networks](https://github.com/sekwiatkowski/awesome-capsule-networks)

- [Contrastive-Learning](https://github.com/HobbitLong/PyContrast/blob/master/AWESOME_CONTRASTIVE_LEARNING.md)

- [Data Augmentation](https://github.com/AgaMiko/data-augmentation-review)

- [Emebedded AI](https://github.com/ysh329/awesome-embedded-ai)

- GAN(Generative Adversarial Networks)

  - [GAN-Case-Study](https://github.com/pshams55/GAN-Case-Study)

  - [really-awesome-gan](https://github.com/nightrome/really-awesome-gan)

  - [AdversarialNetsPapers](https://github.com/zhangqianhui/AdversarialNetsPapers)

  - [the-gan-zoo](https://github.com/hindupuravinash/the-gan-zoo)

  - [Keras-GAN](https://github.com/eriklindernoren/Keras-GAN)

  - [gans-awesome-applications](https://github.com/nashory/gans-awesome-applications): Curated list of awesome GAN applications and demo

  - [image-to-image translation](https://github.com/weihaox/awesome-image-translation)

  - [GAN Inversion](https://github.com/weihaox/awesome-image-translation/blob/master/awesome-gan-inversion.md)

- [Graph Neural Networks(GNN)](https://github.com/thunlp/GNNPapers)

- [Semi-Supervised Learning](https://github.com/yassouali/awesome-semi-supervised-learning)

- [SLAM](https://github.com/kanster/awesome-slam)

  - [SLAM List](https://github.com/OpenSLAM/awesome-SLAM-list)

  - [VSLAM](https://github.com/tzutalin/awesome-visual-slam)

  - [SLAM(Chinese)](https://github.com/YiChenCityU/Recent_SLAM_Research)

  - [SLAM Datasets](https://github.com/youngguncho/awesome-slam-datasets)

  - [SFM-Visual-SLAM](https://github.com/marknabil/SFM-Visual-SLAM)

  - [SLAM Resources](https://github.com/ckddls1321/SLAM_Resources)

  - [wuxiaolang](https://github.com/wuxiaolang)/[Visual_SLAM_Related_Research](https://github.com/wuxiaolang/Visual_SLAM_Related_Research)

- [Reinforcement Learning](https://github.com/aikorea/awesome-rl)

     - [Implementation of Reinforcement Learning Algorithms](https://github.com/dennybritz/reinforcement-learning)

     - [Reinforcement Learning Chinese](https://github.com/wwxFromTju/awesome-reinforcement-learning-zh)：中文整理的强化学习资料

- [Transfer Learning](https://github.com/jindongwang/transferlearning)

- [Trajectory Prediction](https://github.com/jiachenli94/Awesome-Interaction-aware-Trajectory-Prediction)

- [Zero-Shot Learning](https://github.com/chichilicious/awesome-zero-shot-learning)

- Few-Shot Learning

     - [Duan-JM/Few-Shot Learning](https://github.com/Duan-JM/awesome-papers-fewshot)

     - [e-271/Few-Shot Learning](https://github.com/e-271/awesome-few-shot-learning)

- Federated Learning

     - [poga/Federated Learning](https://github.com/poga/awesome-federated-learning)

     - [Federated Computing/Learning](https://github.com/tushar-semwal/awesome-federated-computing)

     - [ChanChiChoi/Federated Learning](ChaoChiChoi/Federated Learning)

- Meta-Learning

     - [Meta-Learning1](https://github.com/dragen1860/awesome-meta-learning)

     - [Meta-Learning2](https://github.com/sudharsan13296/Awesome-Meta-Learning)

- [Open Set Recognition](https://github.com/iCGY96/awesome_OpenSetRecognition_list)

- Self-Supervised

     - [jason718/Self-Supervised](https://github.com/jason718/awesome-self-supervised-learning)

     - [Sungman-Cho/Self-Supervised]( https://github.com/Sungman-Cho/Awesome-Self-Supervised-Papers )

     - [wvangansbeke/Self-Supervised-Learning-Overview](wvangansbeke/Self-Supervised-Learning-Overview)

- [Graph Classification](https://github.com/benedekrozemberczki/awesome-graph-classification)

- [Incremental Learning](https://github.com/xialeiliu/Awesome-Incremental-Learning)

- [AutoML](https://github.com/hibayesian/awesome-automl-papers)

     - [AutoML Survey](https://github.com/DataSystemsGroupUT/AutoML_Survey)

     - [AutoML-and-Lightweight-Models](https://github.com/guan-yuan/awesome-AutoML-and-Lightweight-Models)

     - [NAS](https://github.com/D-X-Y/Awesome-NAS)

     - [Architecture Search](https://github.com/markdtw/awesome-architecture-search)

     - [LITERATURE ON NEURAL ARCHITECTURE SEARCH](https://www.automl.org/automl/literature-on-neural-architecture-search/)

- [Model Compression](https://github.com/cedrickchee/awesome-ml-model-compression)

     - [EfficientDNNs](https://github.com/MingSun-Tse/EfficientDNNs)

     - [Model Compression and Acceleration](https://github.com/memoiry/Awesome-model-compression-and-acceleration)

     - [Neural Network Pruning](https://github.com/he-y/Awesome-Pruning)

- [Binary Neural Networks](https://github.com/michaeltinsley/awesome-binary-neural-networks) 

-  [Multimodal Research](https://github.com/Eurus-Holmes/Awesome-Multimodal-Research)

-  [Multimodal Machine Learning](https://github.com/pliang279/awesome-multimodal-ml)

- [Neural Rendering](https://github.com/xiaweihao/awesome-neural-rendering)

- [NeRF](https://github.com/yenchenlin/awesome-NeRF)

- [Domain Adaptation](https://github.com/zhaoxin94/awsome-domain-adaptation)

- [Robotics](https://github.com/kiloreux/awesome-robotics)

- [Recommender Systems](https://github.com/robi56/Deep-Learning-for-Recommendation-Systems)

- Autonomous Vehicles

     - [Autonomous Vehicles](https://github.com/takeitallsource/awesome-autonomous-vehicles)

     - [Autonomous Vehicles-CH]( https://github.com/DeepTecher/awesome-autonomous-vehicle )

     - [Lidar Point cloud processing for Autonomous Driving](https://github.com/beedotkiran/Lidar_For_AD_references)

- [Anomaly Detection](https://github.com/yzhao062/anomaly-detection-resources)

- [Yochengliu/Point Cloud Analysis](https://github.com/Yochengliu/awesome-point-cloud-analysis)

- [NUAAXQ/Point Cloud Analysis](https://github.com/NUAAXQ/awesome-point-cloud-analysis-2020)

- [3D Point Clouds](https://github.com/QingyongHu/SoTA-Point-Cloud)

- [Affective_Computing](https://github.com/suzana-ilic/Deep_Learning_Affective_Computing)

- Knowledge Distillation

     - [Knowledge Distillation(dkozlov)](https://github.com/dkozlov/awesome-knowledge-distillation)

     - [Knowledge Distillation(FLHonker)](https://github.com/FLHonker/Awesome-Knowledge-Distillation)

- [Click-Through Rate Prediction](https://github.com/shenweichen/DeepCTR)

- [Label Noise](https://github.com/subeeshvasu/Awesome-Learning-with-Label-Noise)

- [VAE](https://github.com/matthewvowels1/Awesome-VAEs)

- [Imbalanced Learning](https://github.com/ZhiningLiu1998/awesome-imbalanced-learning)



# Programming Languages

- [C](https://notabug.org/koz.ross/awesome-c)

- [C++](https://github.com/fffaraz/awesome-cpp)

- [Python](https://github.com/vinta/awesome-python)

- [JAVA](https://github.com/akullpp/awesome-java)

- [JavaScript](awesome-javascript)

- [Julia](https://github.com/svaksha/Julia.jl)

- [MATLAB](https://github.com/uhub/awesome-matlab)

- [R](https://github.com/qinwf/awesome-R)



# Framework

- [TensorFlow](https://github.com/jtoy/awesome-tensorflow)

  - [TensorFlow From Zero To- One](https://github.com/amusi/TensorFlow-From-Zero-To-One)

  - [TensorFlow Lite](https://github.com/margaretmz/awesome-tflite)

- [PyTorch](https://github.com/bharathgs/Awesome-pytorch-list)

  - [PyTorch From Zero To- One](https://github.com/amusi/PyTorch-From-Zero-To-One)

- [Keras](https://github.com/fchollet/keras-resources)

- [MXNet](https://github.com/chinakook/Awesome-MXNet)

- [Caffe](https://github.com/MichaelXin/Awesome-Caffe)

- [Torch](https://github.com/carpedm20/awesome-torch)

- [Chainer](awesome-chainer)



# Datasets

- [Segmentation & Saliency detection](https://github.com/lartpang/awesome-segmentation-saliency-dataset)

# AI Career

- [Awesome Software Engineering for Machine Learning](https://github.com/SE-ML/awesome-seml)