Vansh Sachdeva is a skilled data analyst and developer with expertise in predictive modeling, data visualization, and software development. He has recently worked on a Customer Churn Prediction Model and developed Sales & Customer Dashboards using Tableau. Proficient in Java (OpenJDK 21), Python, and data analytics, Vansh combines analytical thinking with technical proficiency to deliver data-driven insights. His work demonstrates a keen ability to translate complex data into actionable solutions, making him an asset in data science and business intelligence projects.
My GPA In CBSE 10th Board Was 9.4 Out Of 10.
multiple-page dynamic websites were created to enhance web-development skills and concepts.
Tech: HTML5, CSS, Bootstrap, JavaScript, JQuery, Ajax, Django, SQLite
multiple-page dynamic websites were created to enhance web-development skills and concepts.
Tech: HTML5, CSS, Bootstrap, JavaScript, JQuery, Ajax
Makes the overall work of the healthcare institute easier and provides better results in mental and women health-related fulfilled problems. Capable of serving 1000+ users simultaneously
Tech: JavaScript, ReactJs, TensorFlow, Sklearn, Kaggle, HTML, CSS.
Developed a project focusing on the crucial aspect of reducing the risk of serious mental disease, which is mental health prediction, and how it can be used as a theoretical foundation to develop plans for behavioural therapies for healthcare workers
in the department of public health. Using a database with 10,000 records
Tech: Python, Keras, Intel Extension for Scikit Learn, Scikit Learn, Kaggle
Performance metrics for comparison used are Accuracy, recall And Precision of results
Cryptographic applique - Building a decentralized messaging app using the Ethereum blockchain. capable of serving 100 users simultaneously at the lowest gas price
Tech: JavaScript, ReactJs, Web3, Solidity, Ganache, truffle, Infura API.
Comparison of performance of different machine learning algorithms such as artificial neural networks, sample vector machine, decision tree, Logistic regression, Kth nearest neighbour, naive bayes,random forest classification on redit card fraud detection.
Performance metrics for comparison used are Accuracy, recall And Precision of results
Plagiarism & Spam Checker is a project designed to mainly check the “common content” between the Content stored and the content submitted by the user. It also lists out the Spam/Inappropriate words from the submitted work.
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