Vivek Neekhra

With two years experience working as a data scientist and more than ten years of strong academic background, I strive to bring high-quality business intelligence solutions to businesses seeking higher efficiency. With expertise in advanced Statistical Algorithms, Python, Machine Learning and forecasting, and have also worked on over 1150 high performance parallel processing applications using MySQL.

Credit Card Fraud Detection - Machine Learning with Python

The dataset contains transactions made by credit cards in September 2022 by European cardholders. This dataset presents transactions that occurred in two days, where we have 492 frauds out of 284,807 transactions. The dataset is highly unbalanced, the positive class (frauds) account for 0.172% of all transactions. It contains only numerical input variables which are the result of a PCA transformation.

OTP Verifier System - Python

Developed a robust OTP (One-Time Password) verifier system using Python. Implemented secure authentication mechanisms to validate OTP codes generated through various methods like SMS, email, or authenticator apps. Employed industry-standard encryption techniques to ensure data integrity and confidentiality. Designed with a focus on efficiency and scalability, the system provides seamless integration into existing authentication workflows. This project showcases proficiency in Python programming, security protocols, and software development best practices.

Laptop Price Prediction - Machine Learning

Developed a machine learning model using Python to predict laptop prices based on various features such as specifications, brand, and market trends. Employed data preprocessing techniques to clean and prepare the dataset for analysis. Utilized machine learning algorithms including regression and ensemble methods to build an accurate predictive model. Conducted thorough evaluation and fine-tuning of the model to optimize performance. This project demonstrates proficiency in Python programming, data analysis, and machine learning techniques, with a focus on real-world application in the domain of pricing prediction.

Retail Sales Analysis Report - MySQL, Numpy Pandas

Leveraged Python programming along with the powerful data manipulation libraries NumPy and Pandas to perform comprehensive analysis on retail sales data. Conducted data cleaning, preprocessing, and exploratory data analysis to gain insights into sales trends, customer behavior, and product performance. Utilized advanced statistical techniques and visualization tools to uncover patterns and correlations within the dataset. Implemented predictive models to forecast sales and optimize inventory management strategies. This project showcases proficiency in Python programming, data analysis, and utilization of key libraries for extracting actionable insights in the retail domain.

Python Advanced