Yuvraj Singh Chauhan

I am Yuvraj Singh Chauhan undergoing B.Tech third year, pursuing Computer Science and Engineering from SRM University of Science and Technology. I am a very hardworking and ambitious person. I have a great passion for AI, software development and modern technologies. I have a very creative mind in designing and I like working in an organized manner. I always plan ahead to make sure I manage my time

Python Core from Sololearn

Telco Churn Analytics (ML) made using Numpy, Pandas, Matplotlib and Linear Regression.

• For Telco companies it is key to attract new customers and at the same time avoid contract terminations (churn) to grow their revenue generating base. Looking at churn, different reasons trigger customers to terminate their contracts.
• Churn analytics provides valuable capabilities to predict customer churn and also define the underlying reasons that drive it. The churn metric is mostly shown as the percentage of customers that cancel a product or service within a given period.
• Telcos apply machine learning models to predict churn on an individual customer basis and take counter measures such as discounts, special offers or other gratifications to keep their customers. A customer churn analysis is a typical classification problem within the domain of supervised learning.
• Link - https://github.com/yuvrajsinghchauhan/Telco-Churn-Analysis-ML-.git

Amazon Customer Review (NLP) made using Numpy, Pandas, Matplotlib and Sentiment Intensity Analyzer

• Sentiment Analysis is one of the common research areas which performs Natural Language Processing (NLP) tasks for the purpose to extract subjective information by analyzing text data written by users.
• In this program, we aim to perform a sentiment analysis of product reviews written by online users from Amazon. This problem will be viewed as a multi-classification process and we seek to predict the sentiment scale of the user reviews based on machine learning classifiers.
• Link - https://github.com/yuvrajsinghchauhan/Amazon-Customer-Review-NLP-.git

Human Attack Prediction (DL) made using Numpy, Pandas, Matplotlib and Keras

• Nowadays, health diseases are increasing day by day due to life style, hereditary. Especially, heart disease has become more common these days.
• In health care system there is large amount of data but poor in knowledge. The reason behind it is lack of effective analysis system. Because of this data mining is used for the extracting and analyzing the knowledge.
• Numbers of data mining techniques are used like but neural network is one of the most important techniques in data mining. We use the Intelligent Algorithm i.e., ANN (Artificial Neural Network). By using data mining techniques, it takes less time for the prediction of the disease with more accuracy.
• Link -https://github.com/yuvrajsinghchauhan/Human-Attack-Prediction-DL-.git

IQ-Chess made using Javascript, CSS + HTML

• The main purpose of this report is to describe the web-based chess game developed by us named “IQ-Chess”.
• Game rules and its functioning on AI and the encryption technique and detailed explanation about why we this this game is the best example in terms of applications for AI.
• Link - https://smart-chess-ai.netlify.app/

Detection of Human Presence made using Numpy, SQL and CV2

• Over the recent years, detecting human beings in a video scene of a surveillance system is attracting more attention due to its wide range of applications.
• This project aims to track the number of people present at a place and can be used in stores, restaurants, malls, etc. to get data on how many visitors enter a store and at what time.
• Link - https://github.com/yuvrajsinghchauhan/Detection-of-Human-Presence.git/