TASK:1 📊Stock Market Analysis 📈 + Prediction using LSTM

In this notebook, we will discover and explore data from the stock market, particularly some technology stocks (Apple, Amazon, Google and Microsoft). We will learn how to use yfinance to get stock information, and visualize different aspects of it using Seaborn and Matplotlib. We will look at a few ways of analyzing the risk of a stock, based on its previous performance history. We will also be predicting future stock prices through a Long Short Term Memory (LSTM) method.

TASK:2 Titanic Classification Predication 📈

Predicting the Survival of Titanic Passengers:

I will go through the whole process of creating a machine learning model on the famous Titanic dataset, which is used by many people all over the world. It provides information on the fate of passengers on the Titanic, summarized according to economic status (class), sex, age and survival. We will do some basic data analysis, then some visulaization on the dataset, and in the end-use some of the popular models for prediction.

TASK:3 Number Recognition 🖋️

In this notebook, we will harness the MNIST dataset to construct a handwritten digit recognition application. To achieve this, we will utilize a specialized type of deep neural network known as Convolutional Neural Networks 🧠. At the conclusion, we will also create a Graphical User Interface (GUI) where you can directly sketch a digit and instantly recognize it 🖋️.