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Recurrent Neural Networks — How Models Learn from Sequences (RNN, LSTM, GRU)

Some data isn’t static — it comes in sequences. Text, speech, time series, and signals all depend on order.

In this video, we explain Recurrent Neural Networks from first principles. What RNNs are, why simple RNNs struggle, and how LSTMs and GRUs solve the problem of learning long-term dependencies.

You’ll learn:
• What Recurrent Neural Networks (RNNs) are
• Why sequence data needs memory
• What problem LSTMs were designed to solve
• How GRUs simplify LSTMs
• Where RNNs, LSTMs, and GRUs are used in practice

This video is part of Notebook Learning, a channel focused on clear, visual explanations of complex topics in Data Science, Machine Learning, AI, and NLP.

Whether you’re a beginner, student, or developer, this video will help you understand how models learn from sequences in just a few minutes.

📘 New five-minute explainer videos coming regularly.

#RNN #LSTM #GRU #DeepLearning #NeuralNetworks #NLP #TimeSeries #AI #NotebookLearning

Видео Recurrent Neural Networks — How Models Learn from Sequences (RNN, LSTM, GRU) канала Notebook Learning
machine learning data science artificial intelligence deep learning neural networks natural language processing large language models llm engineering prompt engineering generative ai ai agents autonomous agents agentic ai langchain langgraph retrieval augmented generation rag systems computer vision transformers multimodal ai applied machine learning ml engineering
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15 февраля 2026 г. 17:30:41
00:05:48
Notebook Learning
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