STOCK-MARKET-ANALYSIS-PROJECT-

To predict Reliance stock prices using Python, you can utilize machine learning models such as linear regression, support vector machines, or recurrent neural networks. The process involves collecting historical stock price data, cleaning and preprocessing the data, building and training the prediction model, and then evaluating its performance. Python libraries such as pandas for data manipulation, scikit-learn for machine learning models, and TensorFlow or Keras for neural networks can be used for implementation. However, it's important to note that stock price prediction is highly complex and subject to numerous unpredictable factors, so the accuracy of such predictions may be limited.