@villagelife8882: PART 3 ! After all these years, they still wake up together every morning | A quiet life in an Iranian village 🌎 #village #cooking #country #food #viralvideo🙏🙏🙏

Village Kitchen 🌎

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Thursday 10 September 2026 23:37:54 GMT

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. A :

🌺🌺🌺🌺رو

2026-09-11 07:28:16

1

tofiq Bərdəli :

👍👍👍👍

2026-10-04 19:50:15

1

Гульнара Жуковская :

🥰🥰🥰

2026-09-14 18:01:30

1

Meuss borom darou noreyni :

👍👍👍

2026-09-11 17:30:35

1

muhammad huassain4923 :

🥰🥰🥰

2026-09-11 00:47:03

1

Emil Memmedov :

😳😳😳

2026-09-11 04:18:27

1

Nasrin :

🌺🌹❤️

2026-10-07 08:17:04

1

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#recuerdos

The Thought Process of a Data Scientist 👩‍💻 I didn’t start by picking a neural network. I started by evaluating the data and the pipeline. I explored multiple datasets, including the classic Kaggle Cats vs Dogs set, but the moment I realized how much of the “modeling” would turn into filename parsing, manual split logic, and opportunities for silent bugs, I switched to TensorFlow Datasets and used the Oxford-IIIT Pet dataset for its structured labels and reproducible setup. From there, the architecture choices were about alignment, not complexity: a pretrained MobileNetV2 backbone to reuse strong visual features, a lightweight classification head to adapt those features to a simple cat vs dog decision, and a two-stage training process where we first freeze the backbone to stabilize learning, then fine-tune the top layers with a smaller learning rate to improve performance without destroying what the model already knows. And instead of relying on accuracy alone, I tracked metrics that answer different questions about behavior and tradeoffs because the goal isn’t just a high score, it’s a model you can actually understand and trust. Full code: https://tinyurl.com/CNNAnimals #ml #machinelearning #tensorflow #python #datascience

The Thought Process of a Data Scientist 👩‍💻 I didn’t start by picking a neural network. I started by evaluating the data and the pipeline. I explored multiple datasets, including the classic Kaggle Cats vs Dogs set, but the moment I realized how much of the “modeling” would turn into filename parsing, manual split logic, and opportunities for silent bugs, I switched to TensorFlow Datasets and used the Oxford-IIIT Pet dataset for its structured labels and reproducible setup. From there, the architecture choices were about alignment, not complexity: a pretrained MobileNetV2 backbone to reuse strong visual features, a lightweight classification head to adapt those features to a simple cat vs dog decision, and a two-stage training process where we first freeze the backbone to stabilize learning, then fine-tune the top layers with a smaller learning rate to improve performance without destroying what the model already knows. And instead of relying on accuracy alone, I tracked metrics that answer different questions about behavior and tradeoffs because the goal isn’t just a high score, it’s a model you can actually understand and trust. Full code: https://tinyurl.com/CNNAnimals #ml #machinelearning #tensorflow #python #datascience

2Pac & Bones Part 2 (mashup video) @Cale Brown #foryou #music #2pac

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هي الطبقه ديه اسمها ايه ؟ #الشعب_الصيني_ماله_حل😂😂 #اكسبلور #explore #تيك_توك

هي الطبقه ديه اسمها ايه ؟ #الشعب_الصيني_ماله_حل😂😂 #اكسبلور #explore #تيك_توك

yes CO #sohoney_jr #sohoneyjr #wibgajian #promoguncang1010 @sohoney_jr

yes CO #sohoney_jr #sohoneyjr #wibgajian #promoguncang1010 @sohoney_jr

Introducing ARTPHRO Titanium Steel Necklace & Bracelet 💎 Simple lang pero sobrang elegant tignan. ✨ #fyp #fypシ #artphro

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