Sridhar Nagar's repositories
ML-Roadmap-for-2022
A curated list of Machine learning videos, links, projects and datasets to help you conquer the ML landscape in 6 months
Book-Recommendation-System
During the last few decades, with the rise of Youtube, Amazon, Netflix, and many other such web services, recommender systems have taken more and more place in our lives. From e-commerce (suggest to buyers articles that could interest them) to online advertisement (suggest to users the right contents, matching their preferences), recommender systems are today unavoidable in our daily online journeys. In a very general way, recommender systems are algorithms aimed at suggesting relevant items to users (items being movies to watch, text to read, products to buy, or anything else depending on industries). Recommender systems are really critical in some industries as they can generate a huge amount of income when they are efficient or also be a way to stand out significantly from competitors. The main objective is to create a book recommendation system for users.
Credit_Card_Default_Prediction
This project is aimed at predicting the case of customers default payments in Taiwan. From the perspective of risk management, the result of predictive accuracy of the estimated probability of default will be more valuable than the binary result of classification - credible or not credible clients. We can use the K-S chart to evaluate which customers will default on their credit card payments.
CodeWithSridhar
Config files for my GitHub profile.
computer-science
:mortar_board: Path to a free self-taught education in Computer Science!
Bike-Sharing-Demand-Prediction
Currently Rental bikes are introduced in many urban cities for the enhancement of mobility comfort. It is important to make the rental bike available and accessible to the public at the right time as it lessens the waiting time. Eventually, providing the city with a stable supply of rental bikes becomes a major concern. The crucial part is the prediction of bike count required at each hour for the stable supply of rental bikes.
Score-Prediction-Using-Supervised-ML
Linear Regression with Python Scikit Learn In this section we will see how the Python Scikit-Learn library for machine learning can be used to implement regression functions. We will start with simple linear regression involving two variables. Simple Linear Regression In this regression task we will predict the percentage of marks that a student is expected to score based upon the number of hours they studied. This is a simple linear regression task as it involves just two variables.
Seoul-Bike-Sharing-Demand-Prediction
Currently Rental bikes are introduced in many urban cities for the enhancement of mobility comfort. It is important to make the rental bike available and accessible to the public at the right time as it lessens the waiting time. Eventually, providing the city with a stable supply of rental bikes becomes a major concern. The crucial part is the prediction of bike count required at each hour for the stable supply of rental bikes.
HackerRank-Python
Solution of HackerRank problems by Sridhar
data-science
:bar_chart: Path to a free self-taught education in Data Science!
Play-Store-App-Analysis
An Exploratory Data Analysis (EDA) project on Google Play Store Apps and Reviews.