Develop Artificial Intelligence skills and techniques in GRU, LSTM, Time Series Forecasting, Stock Predictions, and Natural Language Processing (NLP).
Deep Learning: Recurrent Neural Networks in Python online certification is a compelling course presented by an inspiring instructor. The cases are well-chosen, demonstrating foundations through fun, creative projects rather than lecturing on abstract concepts. The course is created by Lazy Programmer Inc. - Artificial intelligence and machine learning engineer and presented by Udemy, an ed-tech organization based in the United States that supports students with the greatest and most up-to-date skills through online courses in more than 180 countries.
As the Deep Learning: Recurrent Neural Networks in Python online training involves complex concepts, candidates should have prior knowledge of the following topics to get the most out of the course: matrix addition, multiplication, basic probability, python coding, Numpy coding, matrix, and vector operations, loading a CSV file. The course also provides 12 hours of prerecorded English lectures and an article for understanding the topics at their own pace.
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Udemy
After completing the Deep Learning: Recurrent Neural Networks in Python certification course, learners will about the fundamentals of machine learning and neural networks, classification, and regression using neural networks, modelling sequence data, time-series data, and modelling text data for NLP to create an RNN using TensorFlow 2. Candidates will learn to create text classification RNN and use embeddings in TensorFlow 2 for natural language processing, use TensorFlow 2 to forecast time series and predict stock prices and returns using LSTMs 2, use a GRU and an LSTM 2
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