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Погружаемся в машинное обучение и Data Science

Показываем как запускать любые LLm на пальцах.

По всем вопросам - @haarrp

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💥 Local and Global GANs with Semantic-Aware Upsampling for Image Generation

Github: https://github.com/Ha0Tang/LGGAN

Paper: https://arxiv.org/abs/2203.00047v1

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

@ai_machinelearning_big_data
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Hello everyone. My name is Andrew and for several years I've been working on to make the learning path for ML
easier.

I wrote a manual on machine learning that
everyone understands - Machine Learning Simplified Book. The main purpose of my book is to build an intuitive
understanding of how algorithms work through basic examples. In order to understand the presented material,
it is enough to know basic mathematics and linear algebra.

After reading this book, you will know the basics of supervised learning, understand complex mathematical models, understand the entire pipeline of a typical ML project, and also be able to share your knowledge with colleagues from related industries and with technical
professionals.


You can read the book absolutely free at the link below:
-> https://themlsbook.com
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⚫️ Beyond 3D Siamese Tracking: A Motion-Centric Paradigm for 3D Single Object Tracking in Point Clouds

Github: https://github.com/ghostish/open3dsot

Paper: https://arxiv.org/abs/2203.01730v1

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

@ai_machinelearning_big_data
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💬 A Text Attention Network for Spatial Deformation Robust Scene Text Image Super-resolution

Github: https://github.com/mjq11302010044/tatt

Paper: https://arxiv.org/abs/2203.09388v2

Dataset:
https://deepchecks.com/blog/

@ai_machinelearning_big_data
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💭 NeuralSpeech is a research project in focusing on neural network based speech processing

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

Paper: https://arxiv.org/pdf/2109.14420v3.pdf

Speech Research: https://speechresearch.github.io/

Dataset:
https://paperswithcode.com/dataset/aishell-1

@ai_machinelearning_big_data
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🔎 BigDetection: A Large-scale Benchmark for Improved Object Detector Pre-training

Github: https://github.com/amazon-research/bigdetection

Paper: https://arxiv.org/abs/2203.13249v1

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

@ai_machinelearning_big_data
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