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yurcash :
Если одна из тем понравилась и помогла в обучении с работой ии , оставляйте реакции - это мотивирует разработчиков форума двигаться в правильном направлении
Сообщение
<blockquote data-quote="yurcash" data-source="post: 34" data-attributes="member: 3"><p><h3></h3>
<p style="text-align: justify"></p>
<p style="text-align: justify"><span style="color: rgb(97, 189, 109)"><span style="font-size: 22px">This section is dedicated to the exploration and practical use of neural networks.</span></span></p>
<p style="text-align: justify">It’s designed for developers, researchers, and AI enthusiasts working with both foundational and cutting-edge architectures — from dense networks and convolutional layers to modern transformers.</p><p></p><p></p><h4><span style="color: rgb(97, 189, 109)">What you’ll find here:</span></h4><p></p><ul>
<li data-xf-list-type="ul">Discussions of key frameworks: <strong>TensorFlow</strong>, <strong>PyTorch</strong>, <strong>Keras</strong>, <strong>ONNX</strong>, and more</li>
<li data-xf-list-type="ul">Architectural deep dives: CNN, RNN, LSTM, GANs, Transformers, BERT, GPT, etc.</li>
<li data-xf-list-type="ul">Fine-tuning, hyperparameter optimization, and model evaluation</li>
<li data-xf-list-type="ul">Data preprocessing, augmentation, and training strategies</li>
<li data-xf-list-type="ul">Supervised, unsupervised, and transfer learning approaches</li>
<li data-xf-list-type="ul">Real-world applications across domains: computer vision, NLP, bioinformatics, robotics</li>
<li data-xf-list-type="ul">Topics on model interpretability, robustness, and reproducibility</li>
</ul><p></p><p>Whether you’re experimenting with architectures or applying neural models to production tasks — this is a space for collaboration, insight, and progress.</p></blockquote><p></p>
[QUOTE="yurcash, post: 34, member: 3"]
[HEADING=2][/HEADING]
[JUSTIFY]
[COLOR=rgb(97, 189, 109)][SIZE=6]This section is dedicated to the exploration and practical use of neural networks.[/SIZE][/COLOR]
It’s designed for developers, researchers, and AI enthusiasts working with both foundational and cutting-edge architectures — from dense networks and convolutional layers to modern transformers.[/JUSTIFY]
[HEADING=3][COLOR=rgb(97, 189, 109)]What you’ll find here:[/COLOR][/HEADING]
[LIST]
[*]Discussions of key frameworks: [B]TensorFlow[/B], [B]PyTorch[/B], [B]Keras[/B], [B]ONNX[/B], and more
[*]Architectural deep dives: CNN, RNN, LSTM, GANs, Transformers, BERT, GPT, etc.
[*]Fine-tuning, hyperparameter optimization, and model evaluation
[*]Data preprocessing, augmentation, and training strategies
[*]Supervised, unsupervised, and transfer learning approaches
[*]Real-world applications across domains: computer vision, NLP, bioinformatics, robotics
[*]Topics on model interpretability, robustness, and reproducibility
[/LIST]
Whether you’re experimenting with architectures or applying neural models to production tasks — this is a space for collaboration, insight, and progress.
[/QUOTE]