Forwarded from Data Science
Deep Learning Interviews book: Hundreds of fully solved job interview questions from a wide range of key topics in AI
📖 Book
@datascienceiot
📖 Book
@datascienceiot
A Transformer-Based Siamese Network for Change Detection
Github: https://github.com/wgcban/changeformer
Paper: https://arxiv.org/abs/2201.01293v1
@ArtificialIntelligencedl
Github: https://github.com/wgcban/changeformer
Paper: https://arxiv.org/abs/2201.01293v1
@ArtificialIntelligencedl
Minimum Viable Study Plan for Machine Learning Interviews
https://github.com/khangich/machine-learning-interview
@ArtificialIntelligencedl
https://github.com/khangich/machine-learning-interview
@ArtificialIntelligencedl
GitHub
GitHub - khangich/machine-learning-interview: Machine Learning Interviews from FAANG, Snapchat, LinkedIn. I have offers from Snapchat…
Machine Learning Interviews from FAANG, Snapchat, LinkedIn. I have offers from Snapchat, Coupang, Stitchfix etc. Blog: mlengineer.io. - khangich/machine-learning-interview
✔️ Python library with Neural Networks for Image Segmentation based on Keras and TensorFlow.
Github: https://github.com/qubvel/segmentation_models
Paper: https://arxiv.org/abs/2201.02107v1
Tasks: https://paperswithcode.com/task/semantic-segmentation
@ArtificialIntelligencedl
Github: https://github.com/qubvel/segmentation_models
Paper: https://arxiv.org/abs/2201.02107v1
Tasks: https://paperswithcode.com/task/semantic-segmentation
@ArtificialIntelligencedl
HuSpaCy: Industrial-strength Hungarian NLP
Github: https://github.com/huspacy/huspacy
Paper: https://arxiv.org/abs/2201.01956v1
Dataset: https://paperswithcode.com/dataset/universal-dependencies
@ArtificialIntelligencedl
Github: https://github.com/huspacy/huspacy
Paper: https://arxiv.org/abs/2201.01956v1
Dataset: https://paperswithcode.com/dataset/universal-dependencies
@ArtificialIntelligencedl
GitHub
GitHub - huspacy/huspacy: HuSpaCy: industrial-strength Hungarian natural language processing
HuSpaCy: industrial-strength Hungarian natural language processing - huspacy/huspacy
🚶 Pedestron is a MMdetection based repository, that focuses on the advancement of research on pedestrian detection.
Github: https://github.com/hasanirtiza/Pedestron
Paper: https://arxiv.org/abs/2201.03176v1
Dataset: https://paperswithcode.com/dataset/citypersons
@ArtificialIntelligencedl
Github: https://github.com/hasanirtiza/Pedestron
Paper: https://arxiv.org/abs/2201.03176v1
Dataset: https://paperswithcode.com/dataset/citypersons
@ArtificialIntelligencedl
⛓ ConvNeXt, a pure ConvNet model constructed entirely from standard ConvNet modules.
Github: https://github.com/facebookresearch/ConvNeXt
Paper: https://arxiv.org/abs/2201.03545v1
Dataset: https://paperswithcode.com/dataset/ade20k
@ArtificialIntelligencedl
Github: https://github.com/facebookresearch/ConvNeXt
Paper: https://arxiv.org/abs/2201.03545v1
Dataset: https://paperswithcode.com/dataset/ade20k
@ArtificialIntelligencedl
👍1
🔩 Prompt-BERT: Prompt makes BERT Better at Sentence Embeddings
Github: https://github.com/kongds/prompt-bert
Paper: https://arxiv.org/abs/2201.04337v1
Dataset: https://paperswithcode.com/dataset/sick
@ArtificialIntelligencedl
Github: https://github.com/kongds/prompt-bert
Paper: https://arxiv.org/abs/2201.04337v1
Dataset: https://paperswithcode.com/dataset/sick
@ArtificialIntelligencedl
📌 Fully Adaptive Bayesian Algorithm for Data Analysis
Github: https://github.com/pablomsanala/fabada
Paper: https://arxiv.org/abs/2201.05145v1
Demo: https://github.com/PabloMSanAla/fabada
@ArtificialIntelligencedl
Github: https://github.com/pablomsanala/fabada
Paper: https://arxiv.org/abs/2201.05145v1
Demo: https://github.com/PabloMSanAla/fabada
@ArtificialIntelligencedl
Transfer Learning for Image Recognition and Natural Language Processing
https://www.kdnuggets.com/2022/01/transfer-learning-image-recognition-natural-language-processing.html
@ArtificialIntelligencedl
https://www.kdnuggets.com/2022/01/transfer-learning-image-recognition-natural-language-processing.html
@ArtificialIntelligencedl
Boundary-aware Self-supervised Learning for Video Scene Segmentation
Github: https://github.com/kakaobrain/bassl
Paper: https://arxiv.org/abs/2201.05277v1
Dataset: https://paperswithcode.com/dataset/movienet
@ArtificialIntelligencedl
Github: https://github.com/kakaobrain/bassl
Paper: https://arxiv.org/abs/2201.05277v1
Dataset: https://paperswithcode.com/dataset/movienet
@ArtificialIntelligencedl
Label-dependent and event-guided interpretable disease risk prediction using EHRs
Github: https://github.com/finnickniu/lerp
Paper: https://arxiv.org/abs/2201.06783v1
Dataset: https://paperswithcode.com/dataset/mimic-iii
@ArtificialIntelligencedl
Github: https://github.com/finnickniu/lerp
Paper: https://arxiv.org/abs/2201.06783v1
Dataset: https://paperswithcode.com/dataset/mimic-iii
@ArtificialIntelligencedl
🧪 Structure-Based Drug-Drug Interaction Detection via Expressive Graph Convolutional Networks and Deep Sets
Github: https://github.com/AstraZeneca/chemicalx
Paper: https://ojs.aaai.org/index.php/AAAI/article/view/7236
Dataset: https://chemicalx.readthedocs.io/en/latest/notes/introduction.html#datasets
@ArtificialIntelligencedl
Github: https://github.com/AstraZeneca/chemicalx
Paper: https://ojs.aaai.org/index.php/AAAI/article/view/7236
Dataset: https://chemicalx.readthedocs.io/en/latest/notes/introduction.html#datasets
@ArtificialIntelligencedl
▪️ Decoupling the Depth and Scope of Graph Neural Networks
Github: https://github.com/facebookresearch/shaDow_GNN
Paper: https://arxiv.org/abs/2201.07858v1
@ArtificialIntelligencedl
Github: https://github.com/facebookresearch/shaDow_GNN
Paper: https://arxiv.org/abs/2201.07858v1
@ArtificialIntelligencedl
GitHub
GitHub - facebookresearch/shaDow_GNN: [NeurIPS 2021]: Improve the GNN expressivity and scalability by decoupling the depth and…
[NeurIPS 2021]: Improve the GNN expressivity and scalability by decoupling the depth and receptive field of state-of-the-art GNN architectures - facebookresearch/shaDow_GNN
💫 GVSoC: A Highly Configurable, Fast and Accurate Full-Platform Simulator for RISC-V based IoT Processors
Github: https://github.com/pulp-platform/pulp-sdk
Paper: https://arxiv.org/abs/2201.08166v1
@ArtificialIntelligencedl
Github: https://github.com/pulp-platform/pulp-sdk
Paper: https://arxiv.org/abs/2201.08166v1
@ArtificialIntelligencedl
Explain NLP Models with LIME
https://www.kdnuggets.com/2022/01/explain-nlp-models-lime.html
@ArtificialIntelligencedl
https://www.kdnuggets.com/2022/01/explain-nlp-models-lime.html
@ArtificialIntelligencedl
A Transformer-Based Feature Segmentation and Region Alignment Method For UAV-View Geo-Localization
Github: https://github.com/dmmm1997/fsra
Paper: https://arxiv.org/abs/2201.09206v1
@ArtificialIntelligencedl
Github: https://github.com/dmmm1997/fsra
Paper: https://arxiv.org/abs/2201.09206v1
@ArtificialIntelligencedl
⭕ Interpretable Control Exploration and Counterfactual Explanation (ICE) on StyleGAN
Github: https://github.com/prclibo/ice
Paper: https://arxiv.org/abs/2201.09689v1
Dataset: https://paperswithcode.com/dataset/celeba
@ArtificialIntelligencedl
Github: https://github.com/prclibo/ice
Paper: https://arxiv.org/abs/2201.09689v1
Dataset: https://paperswithcode.com/dataset/celeba
@ArtificialIntelligencedl
DocEnTr: An End-to-End Document Image Enhancement Transformer
Github: https://github.com/dali92002/docentr
Paper: https://arxiv.org/pdf/2201.10252v1.pdf
Dataset: https://paperswithcode.com/dataset/celeba
@ArtificialIntelligencedl
Github: https://github.com/dali92002/docentr
Paper: https://arxiv.org/pdf/2201.10252v1.pdf
Dataset: https://paperswithcode.com/dataset/celeba
@ArtificialIntelligencedl
👺 Masked Autoencoders: A PyTorch Implementation
Github: https://github.com/facebookresearch/mae
Paper: https://arxiv.org/abs/2111.06377
Dataset: https://paperswithcode.com/dataset/imagenet
@ArtificialIntelligencedl
Github: https://github.com/facebookresearch/mae
Paper: https://arxiv.org/abs/2111.06377
Dataset: https://paperswithcode.com/dataset/imagenet
@ArtificialIntelligencedl
🔝 Omnivore: A Single Model for Many Visual Modalities
Github: https://github.com/facebookresearch/omnivore
Code: https://github.com/facebookresearch/omnivore/blob/main/inference_tutorial.ipynb
Paper: https://arxiv.org/abs/2201.08377
Dataset: https://paperswithcode.com/dataset/epic-kitchens-100
@ArtificialIntelligencedl
Github: https://github.com/facebookresearch/omnivore
Code: https://github.com/facebookresearch/omnivore/blob/main/inference_tutorial.ipynb
Paper: https://arxiv.org/abs/2201.08377
Dataset: https://paperswithcode.com/dataset/epic-kitchens-100
@ArtificialIntelligencedl