Coding LSTM which have Keras and TensorFlow (12.2 or more)

Long Short Term Memory (LSTM) and Gated Recurrent Units (GRU) are two layer types commonly used to build recurrent neural networks in Keras. This video introduces these two network types as a foundation towards Natural Language Processing (NLP) and time series prediction.

Code for This Video:
https://github.com/jeffheaton/t81_558_deep_learning/blob/master/t81_558_class_10_2_lstm.ipynb
Course Homepage: https://sites.wustl.edu/jeffheaton/t81-558/

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In this lesson, you will learn a multi-step time series prediction using RNN LSTM for household power consumption prediction. We will predict the power consumption of the coming week based on the power consumption of past weeks.

Download the working file: https://github.com/laxmimerit/Multi-Step-Time-Series-Prediction-using-RNN-LSTM-for-household-power-consumption

Learn Complete Data Science with these 5 video series.
1. Python for Beginners

2. Machine Learning for Beginners

3. Feature Selection in Machine Learning

4. Deep Learning with TensorFlow 2.0 and Keras

5. Natural Language Processing (NLP) Tutorials
https://www.youtube.com/watch?v=eqG34mp-R3A&list=PLc2rvfiptPSQgsORc7iuv7UxhbRJox-pW

The working code is given in the video description of each video. You can download the Jupyter notebook from GitHub.

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LSTM Neural Connects for Time Show Guess IoT Records Science Web conferencing Jakob Aungiers

LSTM Neural Networks for Time Series Prediction IoT Data Science Conference Jakob Aungiers

Data Science for IoT Conference – London – 26th Jan 2017. Jakob Aungiers discussing the use of LSTM Neural Network architectures for time series prediction .

This Edureka Recurrent Neural Networks tutorial video (Blog: will help you in understanding why we need Recurrent Neural Networks .

The analysis of time series data is a fundamental part of many scientific disciplines, but there are few resources meant to help domain scientists to easily explore .

We’re going to use Tensorflow to predict the next event in a time series dataset. This can be applied to any kind of sequential data. Code for this video: .

LSTM Neural Networks like twitter by the due date Show Guess how to IoT Facts Skill Internet meeting that in fact Jakob Aungiers

Data Science for IoT Conference – London – 26th Jan 2017.
Jakob Aungiers discussing the use of LSTM Neural Network architectures for time series prediction and analysis followed by a Tensorflow/Keras/Python demo.

Slides: https://goo.gl/j9jH4X

GitHub Project: https://github.com/jaungiers/LSTM-Neural-Network-for-Time-Series-Prediction

In reference to blog article: http://www.Jakob-Aungiers.com/articles/a/LSTM-Neural-Network-for-Time-Series-Prediction