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RNN and LSTM || Part 02

RNN and LSTM: Part 02 In this session, I have covered an overview of the LSTM architecture and explained why LSTM is chosen over traditional RNNs. Additionally, I discussed the vanishing gradient problem and the exploding gradient problem. Moreover, each LSTM unit has 3 gates: Forget Gate Input Gate Update Gate In a vanilla RNN, one activation function, tanh, is used, whereas in LSTM, two different activation functions (sigmoid and tanh) are utilized, and so on. #RNNBasics #LSTM #SequentialData #AI #MachineLearning #RNN #ML #DeepLearning #StockPrediction #TextProcessing #RNNBasics #LSTM #SequentialData #AI #MachineLearning #RNN #ML #DeepLearning #StockPrediction #TextProcessing #DataScience #NeuralNetworks #ArtificialIntelligence #TimeSeries #Forecasting #NLP #NaturalLanguageProcessing #DataAnalytics #PredictiveModeling #TechTalk #Innovation #SmartTechnology #AIResearch #MachineIntelligence #DeepTech #FutureOfAI #AIRevolution #TechCommunity #AITrends #LearningModels #AIApplications ✌ Follow me On GitHub GitHub code: https://github.com/sajjadrahman56 Twitter:   / sajjadrahman56   #RNNBasics #LSTM #SequentialData #AI #MachineLearning #RNN #ML #DeepLearning #StockPrediction #TextProcessing #RNNBasics #LSTM #SequentialData #AI #MachineLearning #RNN #ML #DeepLearning #StockPrediction #TextProcessing #DataScience #NeuralNetworks #ArtificialIntelligence #TimeSeries #Forecasting #NLP #NaturalLanguageProcessing #DataAnalytics #PredictiveModeling #TechTalk #Innovation #SmartTechnology #AIResearch #MachineIntelligence #DeepTech #FutureOfAI #AIRevolution #TechCommunity #AITrends #LearningModels #AIApplications #cprogramming #cosoleproject #medicalsystem #programming c #programing #cse #cseengineering