Vishal M.

I am Vishal Mandloi - your Tech Architect, ready to construct digital masterpieces that transcend boundaries! With a wealth of experience and expertise as a Tech Architect, I have dedicated myself to the realms of AI, Machine Learning (ML), Deep Learning, Natural Language Processing (NLP), and various other cutting-edge domains. My mastery extends across the entire AI landscape, encompassing AI application development, ML algorithm design, Deep Learning architecture implementation, NLP advancements, and the intricate craftsmanship of building Limitless Learning Machines (LLMs). Whether you seek meticulous Data Collection & Cleaning, robust Model Building & Training , insightful Model Evaluation & Improvement, or seamless Deployment & Maintenance , I possess the technical prowess to transform your AI visions into reality. Here are a few glimpses into the remarkable AI projects I've developed across various domains: 1. Natural Language Processing (NLP) Project: Domain: Sentiment Analysis and Text Classification Description: Developed an NLP-based solution for sentiment analysis and text classification, allowing businesses to understand customer sentiment and extract valuable insights from large volumes of textual data. Leveraged state-of-the-art NLP techniques, such as word embeddings, recurrent neural networks (RNN), and attention mechanisms. 2. Computer Vision Project: Domain: Object Detection and Image Recognition Description: Created a robust computer vision system for object detection and image recognition in real-time scenarios. Employed convolutional neural networks (CNN) combined with transfer learning to achieve high accuracy. The system was deployed in surveillance applications, enabling real-time object tracking and identification. 3. Machine Learning Project: Domain: Fraud Detection in Financial Transactions Description: Built a machine learning-based solution to detect fraudulent activities in financial transactions. Utilized anomaly detection algorithms, such as Isolation Forest and One-Class SVM, to identify suspicious patterns and anomalies in transactional data. The system achieved a high detection rate while minimizing false positives. 4. Recommender System Project: Domain: Personalized Recommendation Engine Description: Developed a recommender system leveraging collaborative filtering techniques and deep learning models to provide personalized recommendations to users. Incorporated techniques like matrix factorization, content-based filtering, and hybrid approaches to enhance the accuracy and relevance of recommendations. Together, we will construct an AI landscape that revolutionizes your business, harnessing the power of AI to unlock unprecedented opportunities and drive remarkable growth. Let's embark on this extraordinary AI journey!