Eshita Upadhyaya

Focused, analytical-minded with problem solving technique, detail-oriented and proactive mindset to contribute company’s commitment to excellence. Highly-motivated employee with desire to take on new challenges. Strong worth ethic, adaptability and exceptional interpersonal skills. Adept at working effectively unsupervised and quickly mastering new skills.

• AWS cloud practioner
• Internshaala web development training
• Cisco Certified Networking Associate
• Cloud Computing
• C++
• Python
• Designing in Figma

• Best Research Paper Award on 4th International Conference on Smart Systems: Innovation in Computing
• Web Development Training: Learning about advance web development topics which help me understand the topics in detail. A small project was assigned to me, so I made Spotify Clone which help me develop and improve my web-development skills
• Hacker-Rank: Attained the highest rating of 5 stars in HackerRank's Problem Solving category, showcasing a superior aptitude for algorithmic challenges and logical reasoning. Demonstrated consistent excellence and problem solving prowess in a competitive coding environment
• Cisco Training: Getting trained about Advanced Networking Essentials through Packet Tracer and solving problems through it

AI/ML

Hand Gesture Recognition                                                                                         July 2023-Nov 2023

To analyze deep learning models for the project. Here we have focused on three models that is Custom CNN with  data augmentation, Transfer Learning withVGG16 and VGG16 as Feature Extractor. 

The objective is to compare the models base on precision, recall, f1-score and performance matrix base on  classification of ten hand gestures 

The result shows how well the model is performed individually base on its accuracy, efficiency and robustness

Stock Market Prediction                                                                                             Jun 2022 - Oct 2022

To propose a hybrid method that combines historical stock data with sentiment analysis of Twitter data to predict the  stock market index. 

The steps used are preprocessing, hyperparameter tuning, and LSTM modeling to analyze the sentiment oftweets and  forecast Nifty 50 index values. 

The project shows howwell the LSTM model predictsstock pricesfor the NIFTY50 index in terms of accuracy, we  can evaluate model effectiveness and our portfolio’s probability will increase

Mobile and Web Development

SkillBoost                                                                                                                   Jan 2023 - May 2023

An education website created for coders with frontend and backend where user can learn course freely. Technologies used for this website are HTML, CSS, JavaScript, PHP and MySQL

Data Science

WaterQuality Prediction                                                                                              Sep 2021 - Nov2021

To collect and extract rawdata and refine it by using Decision TreeAlgorithm and measure the accuracy to predict  the quality of water