Computer Science and Programming
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Channel for who have a passion for -
* Artificial Intelligence
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3D-aware Conditional Image Synthesis (pix2pix3D)

Pix2pix3D synthesizes 3D objects (neural fields) given a 2D label map, such as a segmentation or edge map

Github:
https://github.com/dunbar12138/pix2pix3D

Paper:
https://arxiv.org/abs/2302.08509

Project:
https://www.cs.cmu.edu/~pix2pix3D/

Datasets:
CelebAMask , AFHQ-Cat-Seg , Shapenet-Car-Edge


@MachineLearning_Programming
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Sarath Kumar
+918940876397 / +918778033930
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2023 lectures are starting in just one day, Jan 9th!

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MIT Introduction to Deep Learning The 2022 lectures can be found here:

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πŸ‘‰ @MachineLearning_Programming
Text2Video-Zero

Text2Video-Zero: Text-to-Image Diffusion Models are Zero-Shot Video Generators

Paper: https://arxiv.org/abs/2303.13439
Video Result: video result link
Source code: https://github.com/picsart-ai-research/text2video-zero

join us: @MachineLearning_Programming
Machine Learning Operations (MLOps) Masterclass

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☎️ Contact:

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+918940876397 / +918778033930
Forwarded from Artificial Intelligence && Deep Learning (Shohruh)
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ImageBind: One Embedding Space To Bind Them All.

PyTorch implementation and pretrained models for ImageBind. For details, see the paper: ImageBind: One Embedding Space To Bind Them All.

ImageBind learns a joint embedding across six different modalities - images, text, audio, depth, thermal, and IMU data. It enables novel emergent applications β€˜out-of-the-box’ including cross-modal retrieval, composing modalities with arithmetic, cross-modal detection and generation.

Source code: https://github.com/facebookresearch/imagebind

Paper: https://arxiv.org/pdf/2305.05665v1.pdf

@deeplearning_ai
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Forwarded from Artificial Intelligence && Deep Learning (Shohruh)
Segment Anything in High Quality

We propose HQ-SAM to upgrade SAM for high-quality zero-shot segmentation. Refer to our paper for more details. Our code and models will be released in two weeks. Stay tuned!

https://github.com/syscv/sam-hq


@deeplearning_ai
MLOps Masterclass

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Learn to Design ML Pipelines to Build, Train,Deploy and Monitor your Machine learning models in a real-time production environment.

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Why you shouldn't miss this Masterclass?
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βœ”οΈDedicated mentoring sessions from industry experts.
βœ”οΈ 10 hours session consisting of theory + Hands-on.
βœ”οΈOne-on-One Debugging Session (Optional)

Schedule:
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Highlights of this Masterclass:
β–ͺ️MLOps Introduction
β–ͺ️Getting started with AWS for Machine Learning
β–ͺ️AWS SageMaker Studio
β–ͺ️CI/CD Tools
β–ͺ️AWS MLOps Tools
β–ͺ️AWS MLOps - Build, Train & deploy ML Model

πŸ”₯ Limited Seats Available!

☎️ Contact:
Sarath Kumar
+918940876397 / +918778033930
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Forwarded from Artificial Intelligence && Deep Learning (Shohruh)
Stanford University has just opened full access to CS224U. One of their immensely popular graduate-level Natural Language Understanding course taught by Professor Christopher Potts.

GitHub: https://github.com/cgpotts/cs224u

YouTube: https://youtube.com/playlist?list=PLoROMvodv4rOwvldxftJTmoR3kRcWkJBp

@deeplearning_ai
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join us: @MachineLearning_Programming
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