HeadStarter AI
Over the next five weeks, I will build five AI projects in five weeks. As my final project, Develop as part of a team of 4, Compete in weekend hackathons, Complete PR from an open source project.
Adroit Global Solutions
Engineered a responsive e-commerce website for a major client, boosting user engagement by 20%. Spearheaded collaboration with the design team. Enhancing customer satisfaction by 15%. Optimized website performance, reducing load times by 30% and improving user experience by 25%.
Technologies: Java Script, Python, SQL, React.
SAP
Developed an application for Transfer Order creation, confirmation, reducing item misplacement by 15%. Streamlined internal logistics with real-time inventory updates, Increasing operational efficiency by 20%. Executed project management in an agile environment, collaborating with cross-functional teams using JIRA.
Technologies: MySQL, Python, Git, .Net, CDK.
>Developed NLP applications such as chatbots and sentiment analysis systems, improving sentiment accuracy by 20%. Deployed techniques like named entity recognition and text classification, enhancing data processing speed by 25%. Familiar with machine learning algorithms and evaluation metrics for NLP tasks.
Technologies: Python, libraries like NLTK, spaCy, and TensorFlow for NLP tasks.
Set up a job portal website with content rendering, increasing user retention by 30%. Implemented features to add and delete job openings, along with managing job descriptions and requirements, improving recruitment efficiency by 25%. Designed an intuitive user interface for easy navigation. Boosting user satisfaction by 20%.
Technologies: HTML, CSS, Java Script, Vue.js, MongoDB.
Engineered Python algorithms to predict house prices in Bangalore with an accuracy of 85%. Conducted data analysis ensuring system scalability and reliability, resulting in a 20% increase in prediction accuracy. Built SQL database for efficient data management and a user-friendly front-end, improving user engagement by 15%.
Technologies: MYSQL, Python, HTML, CSS, PYTorch, TensorFlow.
Developed a project to detect Emotion using using and AI
This identify and analyze emotions expressed in text, speech, or other forms of communication. By processing data from social media posts, customer reviews, emails, or spoken interactions, emotion detection systems can classify emotions such as happiness, sadness, anger, or surprise.
This technology is widely used in customer service to gauge user satisfaction.
Technologies: Python, Deep learning, SVM.