Bank-Customer-Segmentation Bank Customer Segmentation with kmeans, PCA and Encoder decoder. 1. Overview : a. Goal : It’s crucial for marketers to know customer and their needs To design targeted marketing campaign tailored for specific needs. For that they need to perform accurate customer segmentation. b. Challenges Faced : Collection of data from twitter through twitter API Structuring and making sense of unstructured and noisy text data. Data cleaning and preprocessing.

Stocks-Sentiment-Analysis-NLP-LSTM Stocks Sentiment Analysis NLP LSTM 1. Overview Goal Humungous data on social media about a stock which is impossible to go through and make decisions. Leverage technology to gain interesting insights and make better investment decisions. Impact Based on the signals of the model investors can make confident and well informed decisions. Time saved by 95% by leveraging technology. Avoid decision fatigue and analysis paralysis. Challenges Faced Collection of data from twitter through twitter API.

Stock-Price-Prediction In this project, I trained a Ridge regression model and deep neural network model to predict future stock prices. The AI model will be trained using historical stock price data along with volume of transactions. 1. Overview : a. Goal : Based on volume and price data , can we predict stock prices? Why? Because while investing other peoples money we need to be really careful and we need real data to support our decisions rather than intuition b.