rkumar45 Goto Github PK
Type: User
Type: User
Predicting Algae's age using different attributes and Machine Learning Algorithms for Regression Analysis.
Optimizing the best Ads using Reinforcement learning Algorithms such as Thompson Sampling and Upper Confidence Bound.
It is a Advanced Problem of Regression which requires advanced techniques of feature engineering, feature selection and extraction, modelling, model evaluation, and Statistics.
It is an Image Processing Challenge where we have to identify the Aerial Cactus using Deep Learning Techniques. I have used fastai library to make this work even easier.
Using Natural Language Processing, Data Visualizations and Classification Algorithms of Machine Learning
It is a Competition for Regression Challenge held by Kaggle, It is based on a Avito Dataset whose size is 123GB which can be accessed from Kaggle, I have done Data Pre-processing, feature engineering, feature extraction, data visualization, machine learning, stacking and boosting
Using Machine Learning Algorithms for Regression Analysis to predict the sales pattern and Using Data Analysis and Data Visualizations to Support it.
Predicting Prices for the products to be sold on Black Friday in US using Regression Analysis, Feature Engineering, Feature Selection, Feature Extraction and Data analysis - Data Visualizations.
The most basic data set available to practice the concepts of regression analysis and explore the most basic concepts of machine learning
This is Data set to Classify the Benign and Malignant cells in the given data set using the description about the cells in the form of columnar attributes. There are Visualizations and Analysis for Support.
It is Data Science and Machine Learning Competition Hosted by Kaggle where we have to perform multi-class classification on the labels, a very good amount of feature engineering, data preprocessing, data visualizations and modelling is done on the data set to get a good accuracy using random forest and xg boost classifier
Predicting which set of the customers are gong to churn out from the organization by looking into some of the important attributes and applying Machine Learning and Deep Learning on it.
It is a Natural Language Processing Problem where we have to decide the sentiments of the users who reviewed the course. and then classifying the reviews into positive and negative.
It is Based on Anamoly Detection and by Using Deep Learning Model SOM which is an Unsupervised Learning Method to find patterns followed by the fraudsters.
It is from Kaggle Competitions where the training dataset is very small and the testing dataset is very large and we have to avoid or reduce overfiting by looking for best possible ways to overcome the most popular problem faced in field of predictive analytics.
Mining Student's Performances through their results in final and intermediate exams using Machine Learning
This is Project which contains Data Visualization, EDA, Machine Learning Modelling for Checking the Sentiments.
This is a project based on the FIFA World Cup 2019 and Analyzes the Performance and Efficiency of Teams, Players, Countries and other related things using Data Analysis and Data Visualizations
Detecting Frauds in Online Transactions using Anamoly Detection Techniques Such as Over Sampling and Under-Sampling as the ratio of Frauds is less than 0.00005 thus, simply applying Classification Algorithm may result in Overfitting
Analyzing the Factors on which Graduates get Admissions in Abroad and Visualizing some of the most intriguing and interesting patterns followed onto it using Data Analysis and Data Visualizations Using Machine Learning.
Analyzing the Features which leads to heart diseases and visualizing the models' performance and important features using eli5, shap and pdp.
Analyzing the HR Criteria of a Company and how they promote their Employees and keep Balance between them using Data Analytics, Data Visualizations, and Machine Learning Models for Classification Purposes.
In this Data set we are Predicting the Insurance Claim by each user, Machine Learning algorithms for Regression analysis are used and Data Visualization are also performed to support Analysis.
My first Machine Learning Repository, It is based on Classification of three different classes called setosa, virginica and versicolor
L&T Financial Services & Analytics Vidhya presents ‘DataScience FinHack’. where I have predicted whether the customer will be defaulter in the first EMI payment using different algorithms from machine learning
Predicting whether a person who has applied for a loan in a bank would get his/her loan approved or not using Classification Algorithms in Machine Learning, by looking at some common and useful attributes.
Using Apriori Algorithm to do Market Basket Analysis of Customers purchasing behaviours. It can predict what the customer is going to buy next by looking at the products he is buying.
Analyzing the Online Transactions in UK and the countries who are purchase stuff from them and analyzing the reviews from them using NLP and Machine Learning
In this data set we have perform classification or clustering and predict the intention of the Online Customers Purchasing Intention. The data set was formed so that each session would belong to a different user in a 1-year period to avoid any tendency to a specific campaign, special day, user profile, or period.
Analyzing the Suicide Bombing Patterns and seeking some of the most tangled questions with good visualizations with the help of Machine Learning and Data Science.
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.