Long Short Term Memory (LSTM) and how to implement LSTM using Python

What is LSTM? You might have heard this term in the last interview you gave for a Machine Learning Engineer position, or some of your friends might have mentioned using LSTM in their predictive modelling projects. So the big question that may arise here is what is LSTM, the purpose of using LSTM in your projects, what type of projects can be made using the LSTM algorithm, etc. Do not worry. This article will cover the in-depth architecture of LSTM networks, how an LSTM works, and its application in the real world.

In the coming sections of this article, you will understand:

• The architecture of RNNs and problems involved with time series forecasting using RNNs
• Standard LSTM architecture and how to build a network of LSTM cells

What is Time-Series Forecasting?

Time Series Forecasting is a technique of using the time series data values and then using it to make predictions about future values on our historical data points.

Time series forecasting has many applications in the field of medical health(for preventing a disease), finance(for predicting future stock prices), weather forecasting(for predicting the weather in future), etc.

Let our time series data vector be:

T = [[t1], [t2], [t3],…….., [tn]]