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Name: Amit Singh
Type: User
Company: Vellore Institute of Technology
Bio: aspiring Data Scientist and Python/R enthusiast.
Location: Bhopal
Name: Amit Singh
Type: User
Company: Vellore Institute of Technology
Bio: aspiring Data Scientist and Python/R enthusiast.
Location: Bhopal
Course-II of ML Specialization from Stanford Online and DeepLearning.AI taught on Coursera by Andrew Ng
This GitHub repository presents sentiment analysis for Amazon Alexa reviews using Logistic Regression and Naive Bayes classifiers. A hybrid approach combining both models achieves a high test accuracy of 92%-94%. The code allows users to analyze their datasets and contribute to the project's further development.
A self-driving car stimulator built on Unity engine.
Repository for Programming Assignment 2 for R Programming on Coursera
The project I produced for the assignment for 'Course 3: Getting and Cleaning Data, of the Data Science Specialization from Johns Hopkins University on Coursera'.
In this project, we aimed to develop a deep learning model for accurately classifying X-ray images as either pneumonia or COVID cases. The objective was to compare accuracy of different types of CNN, where we used two: DenseNet and MobileNetV2 and acheived an accuracy of something close to 54.5% and later using feature scaling it came close to 85%.
The Leek group guide to data sharing
Fine particulate matter (PM2.5) is an ambient air pollutant for which there is strong evidence that it is harmful to human health. In the United States, the Environmental Protection Agency (EPA) is tasked with setting national ambient air quality standards for fine PM and for tracking the emissions of this pollutant into the atmosphere. Approximatly every 3 years, the EPA releases its database on emissions of PM2.5. This database is known as the National Emissions Inventory (NEI). You can read more information about the NEI at the EPA National Emissions Inventory web site. For each year and for each type of PM source, the NEI records how many tons of PM2.5 were emitted from that source over the course of the entire year. The data that you will use for this assignment are for 1999, 2002, 2005, and 2008.
Plotting Assignment 1 for Exploratory Data Analysis
This repository contains an in-depth Exploratory Data Analysis (EDA) of the Spotify Dataset from 2022. Through insightful visualizations and statistical analysis, we gain valuable insights into trends and patterns within the music industry. Additionally, we apply clustering algorithms to group songs based on their audio features.
This project is focused on developing an efficient and accurate solution for fish species detection using deep learning. Leveraging the MobileNetV2 convolutional neural network architecture, we aimed to classify fish species based on their images.
Participated in the Kaggle "Houses Price Competition" and successfully solved the challenge. Leveraged various machine learning techniques to predict house prices accurately. My solution encompasses data preprocessing, feature engineering, and ensemble models to achieve competitive results.
This project leverages machine learning techniques, including K-Nearest Neighbors (KNN) and Decision Trees, to identify exoplanets in astronomical data. By employing classification algorithms, the code sifts through vast datasets to detect potential exoplanets, aiding astronomers in their search for habitable worlds beyond our solar system.
MASK R-CNN: A UNIFIED FRAMEWORK FOR OBJECT INSTANCE SEGMENTATION AND BEYOND
Welcome to this Repository! This repo various machine learning methods such as Linear and Logistic Regression, KNN, Random Forest, SVM & Naive Bayes for predicting stars and galaxies. The code and models provided here offer insights into celestial objects classification & you can use this as a foundation to dive into astronomical data analysis.
Class Notes for Object Oriented Programming - Python
ransforming untidy data to tidy dataset using R.
R Package for 2D and 3D mapping and data visualization
Course materials for the Data Science Specialization: https://www.coursera.org/specialization/jhudatascience/1
Course-I of ML Specialization from Stanford Online and DeepLearning.AI taught on Coursera by Andrew Ng
This repository is made for peer graded project of Python Project for AI and Development on Coursera
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.