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Artificial Intelligence #6 : LSTM Neural Networks with Keras

Artificial Intelligence #6 : LSTM Neural Networks with Keras
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Link : Artificial Intelligence #6 : LSTM Neural Networks with Keras
Artificial Intelligence #6 : LSTM Neural Networks with Keras. Learn how to create Recurrent Neural Network and LSTMs by using Keras Libraries and Python.by Sobhan N.

What you'll learn

  • You'll know how recurrent neural networks work.
  • You'll know how to make simple neural network in Keras environment.
  • You'll learn how to create LSTM networks using python and Keras
  • You'll know how to increase accuracy and decrease error of recurrent neural networks
  • You'll know how to forecast google stock price with high accuracy
  • You'll learn how to use power of neural networks to forecast temperature of New York.
  • You'll learn how to predict NASDAQ Index by using LSTMs.
  • You'll know how to use power of neural networks to forecast wind speed of New York.

Description
Do you like to learn how to forecast economic time series like stock price or indexes with high accuracy?

Do you like to know how to predict weather data like temperature and wind speed with a few lines of codes?

If you say Yes so read more ...

Artificial neural networks (ANNs) or connectionist systems are computing systems vaguely inspired by the biological neural networks that constitute animal brains. Such systems "learn" to perform tasks by considering examples, generally without being programmed with any task-specific rules.  

A recurrent neural network (RNN) is a class of artificial neural network where connections between nodes form a directed graph along a sequence. This allows it to exhibit temporal dynamic behavior for a time sequence. Unlike feedforward neural networks, RNNs can use their internal state (memory) to process sequences of inputs.

In this course you learn how to build RNN and LSTM network in python and keras environment. I start with basic examples and move forward to more difficult examples.
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