Intraday trading is very common among traders because of its capacity to capitalize on price movements within a relatively short period of time. When it comes to formulating trading strategies, having access to real-time price forecasts for the subsequent few minutes can be of great use to traders. The nature of the stock market is such that it is non-stationary, complicated, noisy, chaotic, dynamic, volatile, and non-parametric. This makes it difficult to make accurate predictions in real time. Even if machine learning models are thought to be useful for stock forecasting, their hyperparameters still need to be tuned using the most recent market data in order to take into account the complexity of the market. In most cases, models are trained and tested in batches, which helps to streamline the process of error correction and accelerate the learning process. In order to ensure a high level of accuracy while making intraday stock forecasts, the models should train simultaneously and forecast for each individual instance as opposed to the entire batch. In this research, we offer a technique to estimate the stock price using the real-time stream of the live market. The strategy is based on two distinct learning approaches: incremental learning and offline–online learning. Both of these learning approaches have their advantages and disadvantages. In incremental learning, the model is retrained after each trading session to ensure that it takes into account the most recent data complexities. On the other hand, in offline-online learning, the model is retrained after each trading session to ensure that it takes into account the most recent data complexities. These techniques were utilized to analyze univariate time series, which were constructed using past stock prices, as well as multivariate time series, which took into account historical stock prices in addition to technical indications. Extensive tests were run on the eight most liquid equities that are listed on the NASDAQ stock exchange in the United States of America and the NSE stock exchange in India, respectively.