AIM-IT4

Financial-Analytics-Assignment-2-Prophet-Model

Financial-Analytics-Assignment-1-AR-1-Model-

Risk-Management-Analysis-using-python-VaR-

Calculating future value at risk for Tesla stocks using historical bootstrp method.

Myntra-reviews-analysis-using-LDA-topic-modelling-in-machine-learning

Nashpy-deomnstration

Finalytics-App

Financial App analysis on the go

Heart-Attack-Prediction-Using-ML

Deployed All Ml algorithms to predict whether patient will have heart disease or not.The best model is logistic regression with approximately 85% accuracy

flying-dog-beers

My-First-Android-App

My-first-App-screen

Prediction-of-iris-data-sets-using-decision-tree-ML-model

Optimum-number-of-clusters-using-python

Marks-Prediction-based-on-study-hours-using-machine-learning.

Exploratory-Data-Analysis

Handwriting-Digits-Recognizer

I got 99.6% accuracy and i used random forest model. Machine is now able to predict the digits

IIM-Data-Science-Notebooks

Here you can see the codes executed by me during my summer internship in IIM Shillong

Data-Science-Projects

GUI-Calculator-App

I created an App which is GUI based calculator using tkinter in python

Pandas-Introduction

here you can find notes of data analysis using pandas

DSA-Codes

Here you can find codes of all data structures and algorithm using C++

stock-price-prediction

In this project, we implement and compare the performance of several machine learning and deep learning algorithms in predicting the US stock market.

Aspect-based-opinion-mining-NLP-with-Python-

Aspect-Based Opinion Mining involves extracting aspects or features of an entity and figuring out opinions about those aspects. It's a method of text classification that has evolved from sentiment analysis and named entity extraction (NER). ABOM is thus a combination of aspect extraction and opinion mining. While opinions about entities are useful, opinions about aspects of those entities are more granular and insightful.