Fundamental Analysis and Technical Analysis are the two subcategories of stock market analysis. Analysing a company's fundamentals involves evaluating its financial performance and current business climate in order to predict how profitable it will be in the future.

The process of technical analysis, on the other hand, entails reading charts and analysing data to pinpoint market trends. We'll concentrate on the technical analysis portion.

The main goal of the project is to create a predictive model that can predict Netflix stock values based on historical performance. In order to manage missing values, outliers, and other anomalies in the data, we subsequently did data cleaning and preprocessing.In order to understand the data and find prospective elements that can aid in stock price prediction, we then performed exploratory data analysis.

To train and test our predictive models, we used a variety of machine learning algorithms, such as Lasso regression, decision trees, Support Vector Machines, K-Nearest Neighbours, Ridge Regression, Gaussian Process Regression, Stochastic Gradient Descent, and Random Forest regressor.The project's findings show that machine learning algorithms can reasonably accurately forecast Netflix stock values while identifying model losses.

Result: