Snake Game using Python and Pygame
Implemented collision detection, score tracking and event handling. Optimized memory utilization.
Tushar Tyagi
Computer Science undergraduate
Ghaziabad, Uttar PradeshSoftware Development and Artificial Intelligence/Machine Learning
2roles
35skills
1education
About
Computer Science undergraduate specializing in Artificial Intelligence and Machine Learning, with foundations in data structures, algorithms, DBMS and software development. Experienced in machine learning models, ANN architectures and efficient algorithmic solutions.
Experience
C++ Programming Virtual Intern
CodeAlpha
Sept 2025 – Oct 2025
Refactored algorithms, reducing complexity from O(n2) to O(n). Optimized dynamic memory management and improved application efficiency by 25%. Debugged and optimized C++ applications, reducing runtime errors by 20%. Leveraged STL data structures to improve execution efficiency. Designed modular architecture using Object-Oriented Programming principles.
C++ Programming Intern
CodSoft
Sept 2025 – Oct 2025
Completed a C++ programming internship involving algorithmic solutions, application optimization and software development.
Education
Ajay Kumar Garg Engineering College
B.Tech, Computer Science and Engineering (AI & ML)
2023 – 2027
CGPA: 7.5/10. Relevant coursework: Data Structures, Algorithms, DBMS, Operating Systems, Computer Networks, Artificial Intelligence and Machine Learning.
Skills
CC++PythonMySQLData Structures and AlgorithmsObject-Oriented ProgrammingDBMSOperating SystemsComputer NetworksSTLMultithreadingRegressionClassificationArtificial Neural NetworksBackpropagationHyperparameter TuningFeature EngineeringCross ValidationLLMsPrompt EngineeringRAGEmbeddingsVector DatabasesFastAPIREST APIsTensorFlowScikit-learnNumPyPandasDockerGitLinuxVS CodeJupyterPygame
Projects
Customer Churn Prediction using ANN
Built an ANN model using TensorFlow on a dataset containing 10,000+ customer records. Achieved 88% prediction accuracy and improved model performance through feature engineering and hyperparameter tuning.
Machine Learning Classification and Regression Models
Developed Logistic Regression and Decision Tree models on datasets with 5,000+ samples. Applied K-Fold Cross Validation, improving precision by 10%, and automated the evaluation pipeline, reducing manual effort by 30%.