This is my virtual data science internship with Bharat Intern! This repository contains two tasks:
In this project, I've built a powerful stock price prediction model for Tesla using LSTM. The model provides precise predictions for Tesla's future closing prices, empowering stakeholders with valuable insights to make informed investment decisions. The code includes visualisation, detailed data analysis and machine-learning algorithms.
I've designed a robust classification model to predict the survival status of passengers on the Titanic using Logistic Regression, Decision Tree, and Random Forest classifiers. By meticulously analyzing the dataset and evaluating model performance, I've gained valuable insights into the effectiveness of different algorithms for this specific classification task.
You can explore the code, data, and results of both projects. They are valuable resources for anyone interested in stock price prediction and classification tasks. These projects provide a hands-on experience with real-world datasets and machine learning techniques.
Note: The 'tesla_stock_data.csv' file in the TASK 1 folder contains the historical stock data for Tesla and is required to successfully run the stock price prediction project.