STEPS: Joint Self-supervised Nighttime Image Enhancement and Depth Estimation (ICRA 2023)
🖥 Github: https://github.com/ucaszyp/steps
⏩ Paper: https://arxiv.org/abs/2302.01334v1
➡️ Dataset: https://paperswithcode.com/dataset/nuscenes
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🖥 Github: https://github.com/ucaszyp/steps
⏩ Paper: https://arxiv.org/abs/2302.01334v1
➡️ Dataset: https://paperswithcode.com/dataset/nuscenes
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🔊 Audio-Visual Segmentation (AVS)
🖥 Github: https://github.com/OpenNLPLab/AVSBench
✅️ Paper: https://arxiv.org/pdf/2301.13190.pdf
⭐️ Project: https://opennlplab.github.io/AVSBench/
✅️ Dataset: https://www.avlbench.opennlplab.cn/download
🔹 Benchmark: https://www.avlbench.opennlplab.cn/
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🖥 Github: https://github.com/OpenNLPLab/AVSBench
✅️ Paper: https://arxiv.org/pdf/2301.13190.pdf
⭐️ Project: https://opennlplab.github.io/AVSBench/
✅️ Dataset: https://www.avlbench.opennlplab.cn/download
🔹 Benchmark: https://www.avlbench.opennlplab.cn/
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OReilly.Fundamentals.of.Deep.Learning.pdf
15.9 MB
Fundamentals of Deep Learning
Designing Next-Generation Machine Intelligence Algorithms
#Book #DL
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Designing Next-Generation Machine Intelligence Algorithms
#Book #DL
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🚀 Slapo: A Schedule Language for Large Model Training
Slapo is a schedule language for progressive optimization of large deep learning model training.
🖥 Github: https://github.com/awslabs/slapo
⭐️Paper: https://arxiv.org/abs/2302.08005v1
💻 Docs: https://awslabs.github.io/slapo/
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Slapo is a schedule language for progressive optimization of large deep learning model training.
pip3 install slapo🖥 Github: https://github.com/awslabs/slapo
⭐️Paper: https://arxiv.org/abs/2302.08005v1
💻 Docs: https://awslabs.github.io/slapo/
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Core.ML.Survival.Guide.pdf
6.9 MB
Core ML Survival Guide: More than you ever wanted to know about mlmodel files and the Core ML and Vision APIs (2020)
#Book #ML
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#Book #ML
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Deploying TensorFlow Vision Models in Hugging Face with TF Serving
https://huggingface.co/blog/tf-serving-vision
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https://huggingface.co/blog/tf-serving-vision
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huggingface.co
Deploying TensorFlow Vision Models in Hugging Face with TF Serving
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
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📡 Learning Visual Representations via Language-Guided Sampling
New approach deviates from image-text contrastive learning by relying on pre-trained language models to guide the learning rather than minimize a cross-modal similarity.
🖥 Github: https://github.com/mbanani/lgssl
⭐️Paper: https://arxiv.org/abs/2302.12248v1
⏩Pre-trained Checkpoints: https://www.dropbox.com/sh/me6nyiewlux1yh8/AAAPrD2G0_q_ZwExsVOS_jHQa?dl=0
💻 Dataset : https://paperswithcode.com/dataset/redcaps
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New approach deviates from image-text contrastive learning by relying on pre-trained language models to guide the learning rather than minimize a cross-modal similarity.
🖥 Github: https://github.com/mbanani/lgssl
⭐️Paper: https://arxiv.org/abs/2302.12248v1
⏩Pre-trained Checkpoints: https://www.dropbox.com/sh/me6nyiewlux1yh8/AAAPrD2G0_q_ZwExsVOS_jHQa?dl=0
💻 Dataset : https://paperswithcode.com/dataset/redcaps
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🖥 pyribs: A Bare-Bones Python Library for Quality Diversity Optimization
A bare-bones Python library for quality diversity optimization.
🖥 Github: https://github.com/icaros-usc/pyribs
⏩ Paper: https://arxiv.org/abs/2303.00191v1
⭐️ Dataset: https://paperswithcode.com/dataset/quality-diversity-benchmark-suite
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A bare-bones Python library for quality diversity optimization.
🖥 Github: https://github.com/icaros-usc/pyribs
⏩ Paper: https://arxiv.org/abs/2303.00191v1
⭐️ Dataset: https://paperswithcode.com/dataset/quality-diversity-benchmark-suite
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what you know about chatGPT?
Do you want us to give you information about this on the channel?
Do you want us to give you information about this on the channel?
Anonymous Poll
80%
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OReilly.Python.in.a.Nutshell.pdf
5.8 MB
Python in a Nutshell: A Desktop Quick Reference, 4th Edition (2023)
#python #2023 #book
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#python #2023 #book
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Hariom_Tatsat,_Sahil_Puri_,_Brad_Lookabaugh_Machine_Learning_and.pdf
13.6 MB
Machine Learning & Data Science Blueprints for Finance From Building
Trading Strategies to Robo-Advisors Using Python
Authors: Hariom Tatsat, Sahil Puri & Brad Lookabaugh (2021)
#ML #book
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Trading Strategies to Robo-Advisors Using Python
Authors: Hariom Tatsat, Sahil Puri & Brad Lookabaugh (2021)
#ML #book
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Packt.Agile.Model-Based.Systems.Engineering.Cookbook.pdf
35.4 MB
Agile Model-Based Systems Engineering Cookbook: Improve system development by applying proven recipes for effective agile systems engineering, 2nd Edition (2023)
#Book #2023
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#Book #2023
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ChatGPT.Prompts.Mastering.pdf
757.3 KB
ChatGPT Prompts Mastering: A Guide to Crafting Clear and Effective Prompts – Beginners to Advanced Guide (2023)
Author: Christian Brown
#book #GPT #2023
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Author: Christian Brown
#book #GPT #2023
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