Shivam Chauhan's Projects
Example notebooks that show how to apply machine learning, deep learning and reinforcement learning in Amazon SageMaker
Compared the Average Temperature of Boston and Global from 1740 to 2013. Check out what does trend look like - The World is getting HOTTER !!!
Final group project where AWS architecture was developed for a medical company which connects patient and doctors.
Data Analysis of sales data of a retail chain BigMart. Performed basic EDA. Applied lasso regression and K-mean clustering.
Exploring data from different domains and answering business questions based on insights & facts from data analysis.
Compare red & white wine. I will try to answer the following questions: Which type of wine (red or white) associated with higher quality? What level of acidity (pH value) receives the highest average rating? Do wines with higher alcoholic content receive better ratings? Do sweeter wines receive better ratings? What is proportion of the quality ratings for each wine type?
All Data Analysis Projects. See topics and link to jupyter notebooks. Exploring data from different domains and answering business questions based on insights & facts from data analysis.
Cheat Sheets
Data Visualization project on Washington DC bike sharing rental data. Used Tableau to create a interactive dashboard and showed meaningful insights on bike sharing business related to time,day,temperature, humidity and more.
The open-source repo for docs.github.com
A company has developed a new e-commerce web page in order to try and increase the number of users who "convert," meaning the number of users who decide to pay for the company's product.
This is my first python package uploaded to pypi
Join the GitHub Graduation Yearbook and "walk the stage" on June 5.
Script that scrapes alert statistics from Nagios and reports them to Graphite
List of All Machine Learning project and link to projects. Solved various problem using machine Learning algorithms.
I have added some HW assignments done in Python for Predictive Analytics course at Northeastern University.
In this project, I have analyzed the data set contains 113,937 loans with 81 variables on loan given ny Prosper. The main objective was to explore the data using visualization through uni-variate, bi-variate and multivariate exploration.
Each time I take challenges, I gain strength, courage, and confidence in the doing. I tried to exhibit the codes I wrote while solving Hackerrank and Leetcode challenges.
Basics of reinforcement learning
A game theoretic approach to explain the output of any machine learning model.
Apache Spark
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent