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@sponsbob29: @DA7_ROBI @Yerri Meiryan keluarga tanpa kk🫶

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Sunday 08 November 2026 00:42:31 GMT
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dzf_10
𝐃𝐙𝐅 • 𝐅𝐄́𝐁𝐑𝐈́ - F :
kanan sopo
2026-11-08 02:15:39
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user815769479
saranghae💕 :
masaallah
2026-11-08 01:53:27
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aisellyeu
Aisel🥰 :
MasyaAllah🤍
2026-11-08 01:07:10
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idah.muhayaroh
idah muhayaroh :
robi💜💜💜💜💜💜💜💪💪💪💪
2026-11-08 00:47:28
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mamaerionay
🇮🇩mamaerio🇹🇼 :
2026-11-08 01:14:33
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Deep Learning is a popular field of machine learning that focuses on neural networks and advanced architectures to learn highly complex representations from data that standard ML techniques struggle to learn. Some common tools, areas of study, and models used in deep learning are: Neural networks and optimization, the building blocks of deep learning. Sequence modeling to process ordered data: - Recurrent neural networks - LSTMs and gating - Sequence-to-sequence models - Attention - Transformers - Language models Computer vision: - Convolutional neural networks - Image classification - Object detection - Image segmentation - Video models Geometric learning to represent structured data: - Graph neural networks - 3D vision - Geometric representations Generative modeling to learn and produce new data: - Autoencoders and VAEs - GANs - Diffusion models - Autoregressive models Modern foundation architectures emerging from the transformer architecture: - Large language models - Vision transformers - Vision-language models - Multimodal models - Foundation models Keep up with AI research with our weekly visual newsletter. Join 10,000+ other AI engineers, researchers and PMs getting clear weekly AI breakdowns (link in bio). #deeplearning #machinelearning #computerscience #datascience #math
Deep Learning is a popular field of machine learning that focuses on neural networks and advanced architectures to learn highly complex representations from data that standard ML techniques struggle to learn. Some common tools, areas of study, and models used in deep learning are: Neural networks and optimization, the building blocks of deep learning. Sequence modeling to process ordered data: - Recurrent neural networks - LSTMs and gating - Sequence-to-sequence models - Attention - Transformers - Language models Computer vision: - Convolutional neural networks - Image classification - Object detection - Image segmentation - Video models Geometric learning to represent structured data: - Graph neural networks - 3D vision - Geometric representations Generative modeling to learn and produce new data: - Autoencoders and VAEs - GANs - Diffusion models - Autoregressive models Modern foundation architectures emerging from the transformer architecture: - Large language models - Vision transformers - Vision-language models - Multimodal models - Foundation models Keep up with AI research with our weekly visual newsletter. Join 10,000+ other AI engineers, researchers and PMs getting clear weekly AI breakdowns (link in bio). #deeplearning #machinelearning #computerscience #datascience #math
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ناس لأجل كرامتها راحت مساجين وناس لأجل مصالحهاباعت شرفها..!!!
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