Stock Prediction : Take stock price of any company you want and predicts its price by using LSTM. Use only Jupyter notebook code.
In these task the data we have used is taking from kaggle :https://www.kaggle.com/datasets/vaibhavsxn/google-stock-prices-training-and-test-data These is the link of data used, I have taken the data of google stock prices for prediction and visualizies the actual value with the pedicted value with the help of Long short-term memory(LSTM model training method).
for this project, I primarily utilized the following tools and technologies: Python for data preprocessing, manipulation, visualization, and model implementation. Jupyter Notebook as the coding environment for interactive development. Keras library to build and train the LSTM model.
Titanic Classification : Make a system which tells whether the person will be save from sinking. What factors were most likely lead to success-socio-economic status, age, gender and more.
In these task the data we have used is taking from kaggle :(https://www.kaggle.com/competitions/titanic/data?select=train.csv) These is the link of data used, I have taken the data of Titanic Classification and represent the accuracy and confuson matrix with the help of Machine Learning. Accuracy : 0.7835820895522388
Number Recognition : Handwritten digit recognition system not only detects scanned images of handwritten digits. Handwritten digit recognition using MNIST dataset is a major project made with the help of Neural Network. It basically detects the scanned images of handwritten digits
The data used here is an in-bulit MNIST data for number recognition.