RNN in Tamil | Deep Learning in Tamil | Vanishing Gradient | Exploding Gradient | Adi Explains скачать в хорошем качестве

RNN in Tamil | Deep Learning in Tamil | Vanishing Gradient | Exploding Gradient | Adi Explains

Welcome to another episode of our Deep Learning in Tamil series! In this video, we take a deep dive into one of the most important topics in neural networks – the drawbacks of Recurrent Neural Networks (RNNs). If you have been following our series, you already know what RNNs are and how they are used for solving problems involving sequences, such as natural language processing, speech recognition, and time series prediction. But just like every technology has limitations, RNNs too come with their own set of challenges. This video, explained fully in Tamil, will help you clearly understand the reasons why RNNs are not always the best choice in deep learning. Many beginners and even intermediate learners often ask: Why do we need LSTMs or GRUs when we already have RNNs? The answer lies in the limitations of RNNs. In this video, we break down these limitations in simple Tamil so that students, college learners, and professionals preparing for placements can get a crystal-clear understanding. We will cover issues like the vanishing gradient problem, the exploding gradient problem, why RNNs struggle with long-term dependencies, why training takes longer due to sequential computation, and why memory capacity is limited in RNNs. All of these drawbacks are explained step by step with examples and intuition, so that you can build a solid foundation in deep learning concepts. Our goal in this series is to make complex deep learning concepts easy to learn in Tamil. For most Tamil learners, deep learning resources are available only in English, which makes it hard to fully grasp the mathematical and intuitive aspects. That’s why we created this dedicated Deep Learning Tutorial in Tamil series. By learning in your own language, you can focus better on the ideas rather than struggling with technical jargon. In this particular episode, we ensure you not only learn the drawbacks of RNNs but also develop a strong motivation for why advanced architectures like LSTM (Long Short Term Memory) and GRU (Gated Recurrent Unit) were introduced in the field. If you are someone who is serious about mastering artificial intelligence, neural networks, or data science, then understanding both the strengths and weaknesses of RNNs is absolutely essential. This video is perfect for students preparing for placements, beginners who are exploring AI for the first time, and even professionals who want to strengthen their fundamentals. By the end of this lesson, you will have a clear idea about why RNNs are not used as widely today and how the deep learning community overcame these challenges with newer models. This Tamil deep learning series covers everything from the basics of neural networks to advanced concepts like CNNs, RNNs, LSTMs, GRUs, Transformers, and more. If you are new here, make sure to check out the previous videos where we introduce RNNs, explain how they work, and walk through their applications. Today’s video acts as the foundation for our upcoming discussions on LSTMs and GRUs, so don’t miss it. If you find this content useful, don’t forget to like, share, and subscribe to the channel. Also, hit the notification bell so you don’t miss the next part of this series. Share this with your friends and classmates who are learning deep learning, so that they too can benefit from Tamil-based explanations of advanced AI topics. Deep Learning in Tamil, RNN Drawbacks, Vanishing Gradient Tamil, Exploding Gradient Tamil, RNN Limitations Tamil, Deep Learning Tutorials Tamil, Neural Networks Tamil, AI Tamil, Machine Learning Tamil, LSTM Tamil, GRU Tamil, Deep Learning Series Tamil #tamil #python #deeplearning #machinelearning #recurrencerelation #maths #education #ai #artificialintelligence