π¦Ύ Free Course: The Hands-on Reinforcement Learning course π
Reinforcement learning is a type of machine learning in which the system under test learns by interacting with some environment.
This is a step-by-step, practical course that will help you learn RL from the very basics.
π» Course: https://www.realworldml.xyz/the-hands-on-reinforcement-learning-course
π₯ Github: https://github.com/Paulescu/hands-on-rl
https://t.iss.one/DataScienceT
Reinforcement learning is a type of machine learning in which the system under test learns by interacting with some environment.
This is a step-by-step, practical course that will help you learn RL from the very basics.
π» Course: https://www.realworldml.xyz/the-hands-on-reinforcement-learning-course
π₯ Github: https://github.com/Paulescu/hands-on-rl
https://t.iss.one/DataScienceT
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TinyLlama-1.1B
π₯ Github: https://github.com/jzhang38/tinyllama
π Paper: https://arxiv.org/pdf/2401.02385v1.pdf
π₯Datasets: https://paperswithcode.com/dataset/mmlu
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π₯ Github: https://github.com/jzhang38/tinyllama
π Paper: https://arxiv.org/pdf/2401.02385v1.pdf
π₯Datasets: https://paperswithcode.com/dataset/mmlu
https://t.iss.one/DataScienceT
π3
Forwarded from ML - DS/DA/DE - AI [Jobs, InterviewPrep]
π° Artificial Intelligence A-Zβ’ 2023: Build an AI with ChatGPT4
π 4.3 - 27972 votes π° Original Price: $74.99
Combine the power of Data Science, Machine Learning and Deep Learning to create powerful AI for Real-World applications!
Taught By: Hadelin de Ponteves, Kirill Eremenko
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π 4.3 - 27972 votes π° Original Price: $74.99
Combine the power of Data Science, Machine Learning and Deep Learning to create powerful AI for Real-World applications!
Taught By: Hadelin de Ponteves, Kirill Eremenko
π First Join Channel : https://t.iss.one/+xIYRmZxpAog5YTdk
βοΈ Link Download: https://t.iss.one/c/1943137813/408
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π₯ Transformers From Scratch
PYTHON
In this notebook we have built a transformer model based on the Attention Is All You Need paper following along with Andrej Karpathyβs fantastic YouTube video: Letβs build GPT.
π Notebook: https://blog.matdmiller.com/posts/2023-06-10_transformers/notebook.html
https://t.iss.one/DataScienceT
PYTHON
In this notebook we have built a transformer model based on the Attention Is All You Need paper following along with Andrej Karpathyβs fantastic YouTube video: Letβs build GPT.
π Notebook: https://blog.matdmiller.com/posts/2023-06-10_transformers/notebook.html
https://t.iss.one/DataScienceT
π9
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π§ BakedAvatar: Baking Neural Fields for Real-Time Head Avatar Synthesis
π₯ Code: https://github.com/buaavrcg/BakedAvatar
π Paper: https://dl.acm.org/doi/10.1145/3618399
β‘οΈ Page: https://buaavrcg.github.io/BakedAvatar/
https://t.iss.one/DataScienceT
git clone https://github.com/buaavrcg/BakedAvatar
cd BakedAvatar
π₯ Code: https://github.com/buaavrcg/BakedAvatar
π Paper: https://dl.acm.org/doi/10.1145/3618399
β‘οΈ Page: https://buaavrcg.github.io/BakedAvatar/
https://t.iss.one/DataScienceT
π8
Forwarded from Data Science Books
These are the best questions and answers to job interviews in all areas currently available for job interviews and study, now available in our channel paid at $10 for the entire content of the channel (a permanent subscription of only $10)
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Pay then request join
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Contact @Hussein_Sheikho
π4π1
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π₯Physics-based Text-to-Motionπ₯
π₯ Code: github.com/jiawei-ren/insactor
π Paper: arxiv.org/abs/2312.17135
β‘οΈ Project: https://jiawei-ren.github.io/projects/insactor/
π₯ Code: github.com/jiawei-ren/insactor
π Paper: arxiv.org/abs/2312.17135
β‘οΈ Project: https://jiawei-ren.github.io/projects/insactor/
π3
Sign Language Understanding
π₯ Github: https://github.com/FangyunWei/SLRT
π Paper: https://arxiv.org/pdf/2401.05336v1.pdf
π₯Datasets: https://paperswithcode.com/dataset/csl-daily
https://t.iss.one/DataScienceT
π₯ Github: https://github.com/FangyunWei/SLRT
π Paper: https://arxiv.org/pdf/2401.05336v1.pdf
π₯Datasets: https://paperswithcode.com/dataset/csl-daily
https://t.iss.one/DataScienceT
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β‘οΈ SigLIP: a better CLIP model
π₯ Github: https://github.com/NielsRogge/Transformers-Tutorials/blob/master/SigLIP/Inference_with_(multilingual)_SigLIP%2C_a_better_CLIP_model.ipynb
π Paper: https://arxiv.org/abs/2303.15343
β‘οΈHF: https://huggingface.co/docs/transformers/main/en/model_doc/siglip
https://t.iss.one/DataScienceT
π₯ Github: https://github.com/NielsRogge/Transformers-Tutorials/blob/master/SigLIP/Inference_with_(multilingual)_SigLIP%2C_a_better_CLIP_model.ipynb
π Paper: https://arxiv.org/abs/2303.15343
β‘οΈHF: https://huggingface.co/docs/transformers/main/en/model_doc/siglip
https://t.iss.one/DataScienceT
π AMIE: A research AI system for diagnostic medical reasoning and conversations
π‘ Blog: https://blog.research.google/2024/01/amie-research-ai-system-for-diagnostic_12.html
π Paper: https://arxiv.org/abs/2401.05654
https://t.iss.one/DataScienceT
π‘ Blog: https://blog.research.google/2024/01/amie-research-ai-system-for-diagnostic_12.html
π Paper: https://arxiv.org/abs/2401.05654
https://t.iss.one/DataScienceT
π4
ViQuAE
π₯ Github: https://github.com/paullerner/viquae
π Paper: https://arxiv.org/pdf/2401.05736v1.pdf
π₯Datasets: https://paperswithcode.com/dataset/imagenet
β¨ Tasks: https://paperswithcode.com/task/cross-modal-retrieval
π₯ Github: https://github.com/paullerner/viquae
π Paper: https://arxiv.org/pdf/2401.05736v1.pdf
π₯Datasets: https://paperswithcode.com/dataset/imagenet
β¨ Tasks: https://paperswithcode.com/task/cross-modal-retrieval
π4
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πΌοΈ DDColor: Towards Photo-Realistic Image Colorization via Dual Decoders π₯
π₯ Code: github.com/piddnad/DDColor
π Paper: arxiv.org/abs/2212.11613
π Colab: https://github.com/camenduru/DDColor-colab
https://t.iss.one/DataScienceT
π₯ Code: github.com/piddnad/DDColor
π Paper: arxiv.org/abs/2212.11613
π Colab: https://github.com/camenduru/DDColor-colab
https://t.iss.one/DataScienceT
π8