Faiq Latheef

Leveraged Python proficiency to achieve a significant 60% growth in data science expertise.
Developed an LLM-powered XML proofreading pipeline with structured error tagging, hallucination filtering and XML-safe injection with an interactive Streamlit UI.
Implemented an AI-driven candidate screening system using RAG and LLMs to extract resume data, match skills against hiring criteria, and automate hiring decisions with confidence-based human review.
Developed a Grounded Intelligence Module (Verifiable RAG) using FastAPI, FAISS, OCR and Gemini to extract evidence-backed answers from medical PDFs with automated truth evaluation.
Built a multi-agent, retrieval-augmented LLM system that converts large books into grounded, structured courses (syllabus, lessons, quizzes) using Planner–Retriever–Writer orchestration for scalable, hallucination-resistant generation.
Developed an end-to-end offline RAG system using LangChain, FAISS, HuggingFace, Ollama and Gradio for document based and general purpose AI chat.
Developed a stock prediction system using ARIMA algorithms, achieving an accuracy rate of 82%, which enhanced investment decision-making.
Constructed and trained an RNN-based model for real-time grammar error detection in a voice system, resulting in an improvement percentage of 15% in errors.
Performed exploratory data analysis (EDA) and visualized statistics for spectral data, leading to an improvement of 20% in identifying key trends.
Implemented DBSCAN clustering to extract meaningful patterns from web-scraped data, enhancing data analysis capabilities by reducing analysis time by 30%.
Utilized Python libraries (requests, Scrapy, Selenium, and Request-Html) to automate web crawling, increasing data acquisition efficiency by a percentage of 50%.
Effectively managed projects using version control (GitHub) and task management tools (GitScrum), ensuring efficient collaboration and code versioning.
Developed test automation scripts to streamline software testing, improving software quality by improving metrics and defect rates by 30%.
Championed a continuous improvement mindset by following and enhancing established software development life cycle (SDLC) processes using Agile methodologies.

Leveraged Python proficiency to achieve a significant 60% growth in data science expertise., Developed various projects leveraging LLM, RAG, FastAPI, FAISS, OCR, Gemini, LangChain, HuggingFace, Ollama, Gradio, ARIMA algorithms, RNN-based model, etc.

Spearheaded a 30% growth in the Machine Learning and Deep Learning domain by leveraging Python and SQL expertise.
Preprocessed and analyzed a plant pest prediction dataset using decision tree algorithms.
The model attained an 87% accuracy rate in identifying potential plant pests, leading to a 15% reduction in crop loss.
Deployed the model as a web application using Django for real-time pest risk assessment, increasing accessibility for farmers.
Integrated a CI/CD pipeline through GitHub to automate testing and deployment, resulting in faster model updates and boosted efficiency.
Preprocessed meteorological data for a weather prediction model trained with the ARIMA algorithm.
The model accomplished a mean absolute error (MAE) of 1 degree Celsius, improving weather forecasting accuracy in the region.
Preprocessed and analyzed agricultural data using techniques like feature scaling and handling missing values.
This improved the model's accuracy by 60%.
Trained the Random Forest algorithm with hyperparameter tuning, resulting in a model that predicted crop yield with accuracy metric R-squared of 0.85.
Explored text summarization techniques like frequency-based algorithms (term frequency-inverse document frequency - TF-IDF) for extracting key sentences from text documents.

Spearheaded a 30% growth in the Machine Learning and Deep Learning domain by leveraging Python and SQL expertise., Developed and deployed plant pest prediction model, weather prediction model, crop yield prediction model, and natural language processing projects.

Drove a remarkable 60% growth in software development proficiency utilizing PHP, C#, and SQL skills, delivering highly efficient and user-friendly web and desktop applications.
Developed a user-friendly online clinic management system that reduced appointment scheduling time by 20% for a medical clinic, improving patient experience and clinic efficiency.
Designed and implemented a scalable e-commerce website with secure payment processing and user accounts, leading to a 15% increase in average order value.
Built a seamless online food ordering, payment, and real-time delivery tracking platform, resulting in a 10% faster average delivery time.
Streamlined library operations with a user-friendly search system, online borrowing capabilities, and inventory management tools, leading to a 20% increase in online book borrowing.
Developed a comprehensive construction management application for project planning, resource allocation, and cost tracking for construction companies, resulting in a 15% reduction in project completion time.
Designed and implemented an integrated system to streamline data flow and communication between multiple departments within an organization, leading to refined collaboration and reduced communication errors.
Created a platform for route optimization, vehicle tracking, and dispatch management for a transportation company, resulting in a 10% increase in delivery efficiency.
Built a system for rental property listing, tenant management, and lease agreement processing for a rental company, leading to a 20% reduction in processing time for lease agreements.