Vishnu Kanduri (vishnukanduri)

vishnukanduri

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Location:Buffalo, New York

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Vishnu Kanduri's repositories

Credit-Risk-Modeling-in-Python

Modeled the credit risk associated with consumer loans. Performed exploratory data analysis (EDA), preprocessing of continuous and discrete variables using various techniques depending on the feature. Checked for missing values and cleaned the data. Built the probability of default model using Logistic Regression. Visualized all the results. Computed Weight of Evidence and price elasticities.

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Time-series-analysis-in-Python

I perform time series analysis of data from scratch. I also implement The Autoregressive (AR) Model, The Moving Average (MA) Model, The Autoregressive Moving Average (ARMA) Model, The Autoregressive Integrated Moving Average (ARIMA) Model, The ARCH Model, The GARCH model, Auto ARIMA, forecasting and exploring a business case.

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Air-quality-index-prediction-using-LSTM

I predict air quality index of a city in China using a Long Short Term Memory (LSTM) neural network. for a year. Executed time series analysis

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Customer-Analytics-in-Python

I use various Data Science and machine learning techniques to analyze customer data using STP framework. I preprocessed the data, performed segmentation, hierarchical clustering, k-means, PCA techniques with a lot of visualizations to segment and understand customer data. I have performed Purchase Analytics (both descriptive analysis and predictive analysis). Used deep learning to enhance my model.

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Trading-Bot

Built a trading bot via Reinforcement Learning using Open-AI Gym and Gym Anytrading environment. Added custom indicators such as Simple Moving Average (SMA), Relative Strength Index (RSI) and On Balance Volume (OBV)

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Web-scraping-and-API-in-Python

Scraped rotten tomatoes. Built a currency converter using exchangeratesapi.io. Used Github API, iTunes API and EDAMAM API for cool and fun stuff

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Visualization-Techniques-for-Data-Science-Machine-Learning

Learn to visualize data and perform animations of data in the best way! Understand different techniques and concepts behind these tools.

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Blog-Post-Summarization

Using summarization pipeline from "Transfomers" to summarize any article.

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emoji-search

Simple React app for searching emoji

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Fashion-Recommendations

Manipulated data to recommend products and improve the company's revenue with 90% accuracy. Optimized clustering of user purchases with best feature combinations based on silhouette score. • Used PySpark, Pandas, Seaborn, and Scikit-learn to implement random forest, logistic regression, decision tree and alternating least squares.

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Generate-Blog-Posts

AI model to generate blog posts on any given topic using transformers and GPT-2.

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HR-Management-App

Created a HR Management App using Excel.

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Introduction-to-Data-Science

Get Started with Data Science. Understand how to apply different Data Science methods to solve real-world problems.

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Introduction-to-Machine-Learning

This repo will house all our course material and code snippets from the Introduction to Machine Learning Class

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Language-Classification-using-Naive-Bayes-in-Python

Classified sentences into one of Slovak, Czech, and English. Implemented relevant preprocessing steps, addressed the class imbalance in training set by employing the learned theory of Naive Bayes Models, and implementing subword units.

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Machine-Learning-in-Python

Learn from scratch about machine learning algorithms with practical examples!

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Movie-Recommendation-Engine

Created a movie recommendation engine using Microsoft Excel

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Population-Analysis

Analyzed population data using Excel

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Rock-paper-scissors

A webapp where you can play the classic game of rock, paper and scissors game online.

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S-P-500-Stock-Analysis

Analyzed everyday data of S & P 500 Stock from July 21, 2019 to July 21, 2020

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ultimate_posts

Ultimate posts for opendatascience telegram channel

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