Love Sharma

Skilled multitasker with superior work ethic and good teamwork, problem-solving and organizational skills. Willing to take on any task to help team. Reliable and dedicated team player with hardworking and resourceful approach.

• LinkedIn : https://www.linkedin.com/in/love-sharma-594309229
• Github : https://github.com/ls228611

• Certified Azure Professional: Expertise in Machine Learning and Azure Portal with 90% Score in Certificate Exam.
• Introduction to Artificial Intelligence(AI): Learned about Artificial Intelligence, Deep Learning and Neural Networks.
• Natural Language Processing in TensorFlow: Acquired hands-on experience in building and deploying NLP models using TensorFlow.
• AWS Academy Cloud Architecting: Acquired in-depth knowledge and skills in cloud architecture and AWS services, contributing to proficiency in designing and implementing scalable, secure, and cost-effective cloud solutions.
• Certificate of participation: Level 1.1: E-Commerce & Tech Quiz of the FLIPKART GRID 5.0 - Software Development Track organised by the Flipkart.
• Certificate of participation: Level 1.2: E-Commerce & Tech Quiz of the FLIPKART GRID 5.0- Software Development Track organised by the Flipkart.

 • Credit Card Fraud Detection (Machine Learning) (September,2022-October,2022): Developed a machine learning model using Logistic   Regression to detect fraud with the accuracy of 95 percent. 

• Movie Recommendation System (Machine Learning) (November,2022-December,2022): Developed a model using machine learning algorithm (Cosine Similarity and TfidfVectorizer) to recommend some movies according to the input given by user. 

• Weather Prediction ( Web Application) (April,2023-May,2023): Utilized HTML, CSS, and JavaScript to design and implement a Weather Prediction web application, providing users with real-time weather forecasts and interactive user interfaces. Demonstrated proficiency in web development and data integration to enhance user experience and accessibility. 

• Hand Written Digit Recognition ( Machine Learning) (August,2023-September,2023): Developed and implemented a handwritten digit recognition system using machine learning, achieving a high accuracy rate on the MNIST dataset. Integrated the model into a userfriendly interface for digit input and recognition. 

• Heart Disease Prediction(Machine Learning) (December,2022-January,2023): Developed a machine learning model to classify cardiovascular disease occurrence that can help diagnosticians reduce misdiagnosis.