💥Grokking Artificial Intelligence Algorithms

⬇️ Download

💥Grokking Deep Reinforcement Learning

⬇️ Download

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🏎 Make Pandas 3 Times Faster with PyPolars

Code : https://www.kdnuggets.com/2021/05/pandas-faster-pypolars.html

Github: https://github.com/pola-rs/polars

User Guide: https://pola-rs.github.io/polars-book

@ai_machinelearning_big_data

You Only 👀 One Sequence

Rethinking Transformer in Vision through Object Detection

Github: https://paperswithcode.com/paper/you-only-look-at-one-sequence-rethinking

Dataset: https://paperswithcode.com/dataset/imagenet

Paper: https://arxiv.org/abs/2106.00666

@ai_machinelearning_big_data

🌏 The FLORES-101 Evaluation Benchmark for Low-Resource and Multilingual Machine Translation

Github: https://github.com/facebookresearch/flores

Paper: https://ai.facebook.com/research/publications/the-flores-101-evaluation-benchmark-for-low-resource-and-multilingual-machine-translation

Facebook blog: https://ai.facebook.com/blog/the-flores-101-data-set-helping-build-better-translation-systems-around-the-world/

@ai_machinelearning_big_data

🤖 DynamicViT: Efficient Vision Transformers with Dynamic Token Sparsification

Project: https://dynamicvit.ivg-research.xyz/

Github: https://github.com/raoyongming/DynamicViT


Paper: https://arxiv.org/abs/2106.02034

@ai_machinelearning_big_data

X5 Group проводит собственное мероприятие X5Tech Future Night о технологиях и бизнесе. Большое летнее офлайн событие объединит на одной площадке разные форматы: лекции, паблик-интервью, бизнес-дебаты, дискуссии и музыкальный оупен-эйр.

В программе есть отдельная секция, посвященная Big Data, а именно тому, как монетизировать данные и превратить их в новые продукты.

Участие бесплатное, регистрируйтесь сейчас, чтобы не пропустить. Количество мест ограничено!

📈 NGBoost: Natural Gradient Boosting for Probabilistic Prediction

Github: https://github.com/stanfordmlgroup/ngboost

Slides: https://drive.google.com/file/d/183BWFAdFms81MKy6hSku8qI97OwS_JH_/view

Paper: https://arxiv.org/abs/2106.03823v1

@ai_machinelearning_big_data

🧠 Yet Another Language Model — нейросетевой языковой алгоритм генерации текстов, разработанный Яндексом


Paper : https://wow.link/Er21

@ai_machinelearning_big_data

👨 TFace: A trusty face recognition research platform

Github: https://github.com/Tencent/TFace

Paper: https://arxiv.org/abs/2106.05519v1

@ai_machinelearning_big_data

Microsoft's FLAML - Fast and Lightweight AutoML

Github: https://github.com/microsoft/FLAML

Code: https://github.com/microsoft/FLAML/tree/main/notebook/

Paper: https://arxiv.org/abs/2106.04815v1

@ai_machinelearning_big_data

✅ Graph Transformer Networks: Learning Meta-path Graphs to Improve GNNs

Github: https://github.com/seongjunyun/Graph_Transformer_Networks

Paper: https://arxiv.org/abs/2106.06218v1

Dataset: https://github.com/Jhy1993/HAN

@ai_machinelearning_big_data

🧩 A Bayesian Analysis of Lego Prices in Python with PyMC3

https://austinrochford.com/posts/2021-06-10-lego-pymc3.html

Lego Price Analysis: https://austinrochford.com/posts/2021-06-03-vader-meditation.html

@ai_machinelearning_big_data

Facebook's Reverse engineering generative models from a single deepfake image

Github: https://github.com/vishal3477/Reverse_Engineering_GMs

Paper: https://arxiv.org/abs/2106.07873

Facebook's blog: https://ai.facebook.com/blog/reverse-engineering-generative-model-from-a-single-deepfake-image/

Dataset: https://drive.google.com/drive/folders/1ZKQ3t7_Hip9DO6uwljZL4rYAn5viSRhu?usp=sharing

@ai_machinelearning_big_data

⬇️ Pysentimiento: A Python toolkit for Sentiment Analysis and Social NLP tasks

Github: https://github.com/pysentimiento/pysentimiento

Paper: https://arxiv.org/abs/2106.09462

English model: https://huggingface.co/finiteautomata/bertweet-base-sentiment-analysis

@ai_machinelearning_big_data

🔍 Advancing computer vision research with new Detectron2 Mask R-CNN baselines

Facebook Ai: https://ai.facebook.com/blog/advancing-computer-vision-research-with-new-detectron2-mask-r-cnn-baselines/

Code: https://github.com/facebookresearch/detectron2/blob/master/MODEL_ZOO.md#new-baselines-using-large-scale-jitter-and-longer-training-schedule

Tensorflow implementation: https://github.com/tensorflow/tpu/tree/master/models/official/detectiona

@ai_machinelearning_big_data

📘 D2L.ai: Interactive Deep Learning Book with Multi-Framework Code, Math, and Discussions

Github: https://github.com/d2l-ai/d2l-en

Book: https://d2l.ai/

Paper: https://arxiv.org/abs/2106.11342v1

@ai_machinelearning_big_data

Cartoon-StyleGan2 🙃 : Fine-tuning StyleGAN2 for Cartoon Face Generation

Github: https://github.com/happy-jihye/Cartoon-StyleGan2

Paper: https://arxiv.org/abs/2106.12445

Colab: https://colab.research.google.com/github/happy-jihye/Cartoon-StyleGan2/blob/main/Cartoon_StyleGAN2.ipynb

@ai_machinelearning_big_data

🔺 Pyramid Vision Transformer

Image classification, object detection, and semantic segmentation tasks

Github: https://github.com/whai362/PVT

Paper: https://arxiv.org/abs/2106.13797v2

@ai_machinelearning_big_data

🔎 Microsoft AutoML - Neural Architecture Search

New one-shot architecture search framework dedicated to vision transformer search

Github: https://github.com/microsoft/AutoML

Paper: https://arxiv.org/abs/2107.00651v1

Models: https://drive.google.com/drive/folders/1NLGAbBF9bA1IUAxKlk2VjgRXhr6RHvRW

Dataset: https://paperswithcode.com/dataset/cifar-10

@ai_machinelearning_big_data

🚀 TensorFlow and PyTorch performance benchmarking in 2021

Habr: https://habr.com/ru/company/ru_mts/blog/565456/

Github: https://github.com/Chifffa/tf_vs_torch_benchmarking

@ai_machinelearning_big_data

🔝 Learning Hierarchical Graph Neural Networks for Image Clustering

Github: https://github.com/dmlc/dgl/tree/master/examples/pytorch/hilander

Paper: https://arxiv.org/abs/2107.01319

Datasets: https://drive.google.com/file/d/1KLa3uu9ndaCc7YjnSVRLHpcJVMSz868v/view

@ai_machinelearning_big_data