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My work focuses on NLP, Computer Vision, Cloud Computing, and deploying ML models at scale.\n---\n## 🔗 Let's Connect\n[](https://www.linkedin.com/in/akshit-sharma-475a94271/) \n[](https://x.com/Akshit_7093)\n---\n## 💻 Skills \n### Languages:\n### ML & AI: \n### Web & Cloud: \n### Tools & Platforms: \n---\n## 📂 Featured Projects \n### 🎬 Movie Genre Classifier\nBuilt using scikit-learn and Flask. Achieved 92% accuracy on a dataset of 10,000 movies. \n🔗 GitHub Repo \n### 💳 Credit Card Fraud Detection\nReduced false positives by 15% using XGBoost and feature engineering on 1 million transactions. \n🔗 GitHub Repo \n### 🗣️ SMS Spam Detection\nNLP-based model with 95% accuracy deployed using Flask. \n🔗 GitHub Repo \n### ☁️ OpenStack Cloud Manager with Gemini\nNatural language interface to manage OpenStack resources using Google Gemini. \n🔗 GitHub Repo \n### 🤖 Universal Website Chatbot\nLlama 3.1 based chatbot with voice assistant via Google TTS. \n🔗 GitHub Repo \n### 🧏 SignEase - Real-Time Sign Language Translator\nVideo calling app with TensorFlow + WebRTC achieving >89% accuracy. \n🔗 GitHub Repo \n---\n## 📊 GitHub Stats\n## 🏆 GitHub Trophies", "pinned_repositories": [ { "name": "SheShield1", "language": "Java", "stars": 1, "forks": 0 }, { "name": "SheShield", "language": "Python", "stars": 0, "forks": 0 }, { "name": "WeCare", "language": "CSS", "stars": 0, "forks": 0 }, { "name": 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React, Node.js, TypeScript, Flask, FastAPI \n●​\nDatabases & Tools: Pandas, NumPy, Matplotlib, MongoDB, Postgre \n●​\nML/AI & Frameworks: TensorFlow, PyTorch, NLP, Computer Vision, Transformers, RAG, LangChain \n●​\nCloud & DevOps: AWS, Google Cloud Platform, OpenStack SDK, Docker, Kubernetes \n●​\nSystems & Fundamentals: Unix/Linux, TCP/IP Networking, Git, Data Structures & Algorithms, Computer Networks \nEXPERIENCE\n \nResearch Intern | Directorate of Research, Government of Arunachal Pradesh​\n​\n \n(August 2025 – Present) \n●​\nDeveloped a low-resource speech-to-speech translation pipeline using Wav2Vec 2.0 for ASR, MarianMT for NMT, and Tacotron 2 \nfor TTS, focusing on endangered languages with context-dependent meanings. \n●​\nOptimised system architecture to reduce translation latency to under 2 seconds, enabling real time deployment for field use. \nDeep Learning Intern | Akanila Technologies ​ ​\n https://github.com/akshit7093/Chatbot-for-websites \n(July 2024 – December 2024) \n●​\nDeveloped a universal chatbot platform by fine‑tuning Llama3.1 LLM using LoRA and integrating RAG with FAISS for \ndomain‑specific retrieval, boosting query accuracy to 90 % and improving response relevance by 25 %. \n●​\nDesigned a flexible Python backend with modular components in FastAPI increasing code reusability to 65% . \n●​\nImplemented automated deployments on AWS EC2, leveraging Docker for containerization and Kubernetes for container \norchestration. \nMachine Learning Intern | CodSoft ​\n https://github.com/akshit7093/CODSOFT \n(August 2024 – September 2024) \n●​\nDeveloped a credit card fraud detection system using XGBoost, analyzing 1 million transaction records. \n●​\nEngineered 20+ features from behavioral and time-series data then trained an XGBoost model on SageMaker to drop false \npositives from 20% to 5% while keeping recall over 90%. \n●​\nBuilt an NLP model for SMS spam detection using Python and scikit-learn, achieving 95% accuracy on test data. \nPROJECT\n \nOpenStack Cloud Management System with Natural Language Interface https://github.com/akshit7093/VM_manager_AgenticAi \n●​\nBuilt a cloud management system interfacing with OpenStack infrastructure APIs. \n●​\nEnabled users to issue natural language prompts (e.g., \"create a server\" or \"delete a volume\"), which an AI agent created using \nLangChain and Google's Gemini-2.5 pro model translated into precise OpenStack API calls. \n●​\nBuilt an interactive CLI and a web app for remote management, featuring resource analytics and container monitoring per VM. \n●​\nDesigned RESTful backend with Fastapi and containerized the application using Docker. \n●​\nTechnologies: Python, OpenStack SDK, Gemini, Fastapi, Docker, LangChain \nSignEase -Video calling platform for individuals with disabilities​ https://github.com/akshit7093/Sign-language-translator.git \n●​\nCreated a video chat application using React and Node.js to enable video communication with ASL translation. \n●​\nImplemented American Sign Language (ASL) detection using MediaPipe for landmarks and an LSTM network in TensorFlow, \nreaching 89% accuracy on a small dataset of 20 videos. \n●​\nReduced latency from 500ms to 180ms using model quantization (TensorFlow Lite) and frame-rate optimization. \n●​\nTechnologies: Python, TensorFlow, WebRTC, React, Node.js, MediaPipe. \nEDUCATION \n \nMaharaja Agrasen Institute of Technology​\n​\n​\n​\n​\n​\n​\n(June 2022 - June 2026) \n●​\nB.Tech. in Computer Science with a specialization in Artificial Intelligence and Data Science \n●​\nCGPA:8.96/10 ​\n​\n​\n​\n​\n​\n​\n​\n \n●​\nRelevant Coursework: Machine Learning, Data Mining, Image Processing, Data Structures and Algorithms, Computer Networks \nCERTIFICATIONS \n \n●​\nData Science (Pwskills) \n●​\nMachine Learning and Deep Learning Specialization (Coursera) \n●​\nAWS Solutions Architect Virtual Experience Program (Forage)  \n●​\nIntroduction to Generative AI (Google) \n●​\nDevelop GenAI Apps with Gemini and Streamlit (Google) \n●​\nPrompt Design in Vertex AI (Google) \nACHIEVEMENTS \n \n●​\nWinner – AceCloud X RTDS Hackathon ‘25", "full_text_preview": "Akshit Sharma \nFinal‑Year B.Tech (AI & Data Science) | Backend & AI/ML Engineer | Cloud‑Native Systems \nakshitsharma7096@gmail.com/ +91 8810248097/Github / Linkedin / LeetCode / CodeForces \nSKILLS\n \n●​\nProgramming Languages: Python, Java, C/C++, JavaScript, SQL, React, Node.js, TypeScript, Flask, FastAPI \n●​\nDatabases & Tools: Pandas, NumPy, Matplotlib, MongoDB, Postgre \n●​\nML/AI & Frameworks: TensorFlow, PyTorch, NLP, Computer Vision, Transformers, RAG, LangChain \n●​\nCloud & DevOps: AWS, Google...", "professional_links": [ "mailto:akshitsharma7096@gmail.com", "https://github.com/akshit7093", "https://www.linkedin.com/in/akshit-sharma-475a94271/", "https://leetcode.com/u/akshitsharma7093/", "https://codeforces.com/profile/akshit7093", "https://github.com/akshit7093/Chatbot-for-websites", 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LangChain Cloud DevOps: AWS, Google Cloud Platform, OpenStack SDK, Docker, Kubernetes Systems Fundamentals: UnixLinux, TCPIP Networking, Git, Data Structures Algorithms, Computer Networks EXPERIENCE Research Intern Directorate of Research, Government of Arunachal Pradesh (August 2025 Present) Developed a low-resource speech-to-speech translation pipeline using Wav2Vec 2.0 for ASR, MarianMT for NMT, and Tacotron 2 for TTS, focusing on endangered languages with context-dependent meanings. Optimised system architecture to reduce translation latency to under 2 seconds, enabling real time deployment for field use. Deep Learning Intern Akanila Technologies https:github.comakshit7093Chatbot-for-websites (July 2024 December 2024) Developed a universal chatbot platform by finetuning Llama3.1 LLM using LoRA and integrating RAG with FAISS for domainspecific retrieval, boosting query accuracy to 90 and improving response relevance by 25 . Designed a flexible Python...", "key_skills": [ "Python", "Java", "Javascript", "React", "Node", "Sql", "Mongodb", "Aws", "Docker", "Kubernetes", "Git", "C++", "Typescript", "Flask", "Tensorflow", "Pytorch", "Data structures", "Algorithms", "Backend" ], "total_hyperlinks": 13, "professional_link_count": 13, "missing_elements": [] }, "errors": {} } }