Update README.md

Author: JordiCorbilla

README.md

@@ -4,7 +4,7 @@ Predicting stock prices using a TensorFlow LSTM (long short-term memory) neural
 
 ## 1) Introduction
 
-Predicting stock prices is a cumbersome task as it does not follow any specific pattern. Changes in the stock prices are purely based on supply and demand during a period of time. In order to learn the specific characteristics of a stock price, we can use deep learning to identify these patterns through machine learning. One of the most well-known networks for series forecasting is [LSTM](https://www.researchgate.net/publication/13853244_Long_Short-term_Memory) (long short-term memory) which is a Recurrent Neural Network (RNN) that is able to remember information over a long period of time, thus making them extremely useful for predicting stock prices. RNNs are well-suited to time series data and they are able to process the data step-by-step, maintaining an internal state where they cache the information they have seen so far in a summarised version. The successful prediction of a stock's future price could yield a significant profit.
+Predicting stock prices is a complex task, as it is influenced by various factors such as market trends, political events, and economic indicators. The fluctuations in the stock prices are driven by the forces of supply and demand, which can be unpredictable at times. To identify patterns and trends in stock prices, deep learning techniques can be used for machine learning. Long short-term memory ([LSTM](https://www.researchgate.net/publication/13853244_Long_Short-term_Memory)) is a type of recurrent neural network (RNN) that is specifically designed for sequence modeling and prediction. LSTM is capable of retaining information over an extended period of time, making it an ideal approach for predicting stock prices. As a result, RNNs are well-suited to time series data, where they process data step-by-step, maintaining an internal state where they store the information they have seen so far in a compressed form. Accurate prediction of a stock's future price can provide significant financial gain to investors.
 
 ## 2) Stock Market Data