Pinned Repositories
Canvas-Grade-Analyzer
Pull Data from Canvas Gradebook and Compute Statistics for Students: Intro to Python at Virginia Tech
Deep-Analysis-of-US-College-System
This semester, in Learning Inference Decisions, I am learning how to conduct thoughtful experiments and analysis with big and noisy data. The course covers Frequentist and Bayesian inference, bootstrap, instrumental variable analysis, multi-arm bandits and Q-learning by using a combination of ML and optimization techniques.
hello-world
Mechanics-of-Blockchain
Course assignements for CS5431 Blockchains, Cryptocurrencies, and Smart Contracts taugh by Ari Juels at Cornell Tech. Course covers topics Bitcoin, Basic Crypto: Hash Functions, Public-Key Cryptography, Transactions/Scripts, Byzantine Agreement, Bitcoin Mining, Permissionless Consenses (Nakamoto Consensus), Proof of Stake, Wallets and Key Management, Privacy in Cryptocurrencies, Smart Contracts, Zero Knowledge Proofs, Privacy Coins, Oracles, DeFi: DEXes, Miner Extractable Value, Criminal SC's and Pyramid Schemes, NFT's, Decentralized Identity
Media-Sentiment-Stock-Analysis
MiniTorch
MiniTorch (https://github.com/minitorch/) is a diy teaching library for machine learning engineers who wish to learn about the internal concepts underlying deep learning systems. It is a pure Python re-implementation of the Torch API designed to be simple, easy-to-read, tested, and incremental. The final library can run Torch code. The project was developed for the course Machine Learning Engineering at Cornell Tech.
Predicting-Employee-Attrition
Automated a rigorous data cleaning and semantic mapping pipeline for various exit-surveys without human intervention. Experimented with alternatives and optimized ML models’ parameters with Scikit-learn, Tensor Flow achieving 80% accuracy. Performed feature importance analysis with Hugging Face NLP to analyze key attrition drivers for future survey improvement. Presented project at the VT ISE Senior Symposium for the department’s clients, alumni board, faculty, and peers.
Recommendation-Systems-Algorithmic-Pricing
Developed predictive ratings to craft personalized recommendation systems with matrix factorization. Dealt with real-world implications: cold start/missing data, capacity constraints and matching in 2-sided marketplaces. Priced under uncertainty by estimating demand using dynamic programming for over-time pricing problems. Worked with data and deployed decision-making models in socio-technical systems; handling user incentives and strategic behavior, networked and decentralized decision-making, and feedback loops between deployed models and future data.
River-Logistics-Optimization-Problem
TextBasedAdventureGame
Text Based Adventure Game
nikhilpereira24's Repositories
nikhilpereira24/Mechanics-of-Blockchain
Course assignements for CS5431 Blockchains, Cryptocurrencies, and Smart Contracts taugh by Ari Juels at Cornell Tech. Course covers topics Bitcoin, Basic Crypto: Hash Functions, Public-Key Cryptography, Transactions/Scripts, Byzantine Agreement, Bitcoin Mining, Permissionless Consenses (Nakamoto Consensus), Proof of Stake, Wallets and Key Management, Privacy in Cryptocurrencies, Smart Contracts, Zero Knowledge Proofs, Privacy Coins, Oracles, DeFi: DEXes, Miner Extractable Value, Criminal SC's and Pyramid Schemes, NFT's, Decentralized Identity
nikhilpereira24/Recommendation-Systems-Algorithmic-Pricing
Developed predictive ratings to craft personalized recommendation systems with matrix factorization. Dealt with real-world implications: cold start/missing data, capacity constraints and matching in 2-sided marketplaces. Priced under uncertainty by estimating demand using dynamic programming for over-time pricing problems. Worked with data and deployed decision-making models in socio-technical systems; handling user incentives and strategic behavior, networked and decentralized decision-making, and feedback loops between deployed models and future data.
nikhilpereira24/MiniTorch
MiniTorch (https://github.com/minitorch/) is a diy teaching library for machine learning engineers who wish to learn about the internal concepts underlying deep learning systems. It is a pure Python re-implementation of the Torch API designed to be simple, easy-to-read, tested, and incremental. The final library can run Torch code. The project was developed for the course Machine Learning Engineering at Cornell Tech.
nikhilpereira24/Predicting-Employee-Attrition
Automated a rigorous data cleaning and semantic mapping pipeline for various exit-surveys without human intervention. Experimented with alternatives and optimized ML models’ parameters with Scikit-learn, Tensor Flow achieving 80% accuracy. Performed feature importance analysis with Hugging Face NLP to analyze key attrition drivers for future survey improvement. Presented project at the VT ISE Senior Symposium for the department’s clients, alumni board, faculty, and peers.
nikhilpereira24/Canvas-Grade-Analyzer
Pull Data from Canvas Gradebook and Compute Statistics for Students: Intro to Python at Virginia Tech
nikhilpereira24/Deep-Analysis-of-US-College-System
This semester, in Learning Inference Decisions, I am learning how to conduct thoughtful experiments and analysis with big and noisy data. The course covers Frequentist and Bayesian inference, bootstrap, instrumental variable analysis, multi-arm bandits and Q-learning by using a combination of ML and optimization techniques.
nikhilpereira24/hello-world
nikhilpereira24/Media-Sentiment-Stock-Analysis
nikhilpereira24/River-Logistics-Optimization-Problem
nikhilpereira24/TextBasedAdventureGame
Text Based Adventure Game