THE FUTURE IS HERE

How to Predict Stock Prices Easily – Intro to Deep Learning #7

We’re going to predict the closing price of the S&P 500 using a special type of recurrent neural network called an LSTM network. I’ll explain why we use recurrent nets for time series data, and why LSTMs boost our network’s memory power.

Coding challenge for this video:
https://github.com/llSourcell/How-to-Predict-Stock-Prices-Easily-Demo

Vishal’s winning code:
https://github.com/erilyth/DeepLearning-SirajologyChallenges/tree/master/Image_Classifier

Jie’s runner up code:
https://github.com/jiexunsee/Simple-Inception-Transfer-Learning

More Learning Resources:
http://colah.github.io/posts/2015-08-Understanding-LSTMs/
http://deeplearning.net/tutorial/lstm.html
https://deeplearning4j.org/lstm.html
https://www.tensorflow.org/tutorials/recurrent
http://machinelearningmastery.com/time-series-prediction-lstm-recurrent-neural-networks-python-keras/
https://blog.terminal.com/demistifying-long-short-term-memory-lstm-recurrent-neural-networks/

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music in the intro is chambermaid swing by parov stelar
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