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Transforming complex AI concepts into practical solutions. Specializing in NLP, Computer Vision, and Cloud AI Engineering.
def build_ai_solution():
model = Transformer(
layers=12,
heads=8,
d_model=768
)
return model.predict(
input_data,
confidence=0.95
)Hey 👋🏼 I'm Muhammad Furqan, a Junior AI Engineer based in Lahore, Pakistan 🇵🇰. With a strong passion for AI, machine learning, and cloud technologies, I thrive on building intelligent solutions that make a real-world impact.
I specialize in developing AI solutions that solve real-world problems. My expertise includes natural language processing, computer vision, and cloud-based AI deployments. I'm passionate about creating intelligent systems that can understand, learn, and adapt to complex scenarios.
Throughout my career, I've worked on various AI projects, from developing chatbots and recommendation systems to implementing computer vision solutions for object detection and recognition. I'm constantly learning and exploring new technologies to stay at the forefront of AI innovation.
When I'm not coding or diving into AI research, I enjoy contributing to open-source projects, participating in AI competitions on Kaggle, and sharing my knowledge through technical blog posts and tutorials.
Sep 2024 – Present
Currently working on real-world AI solutions at Silicon Nexus.
April 2024 – July 2024
Oct 2023 – March 2024
Began my AI journey through online courses and projects, focusing on machine learning, deep learning, and data analysis fundamentals.
Military Podcast is an AI-driven platform built with LangChain and FastAPI, designed to transcribe and analyze military-related podcasts. The system leverages LangChain's document processing capabilities and FastAPI's high-performance API framework to enable efficient content discovery, semantic search, and meaningful insights extraction from audio data.
MathWiz is a personalized AI-powered math question generation platform built using LangChain and FastAPI. The system uses LangChain's LLM integration capabilities to generate adaptive math problems, while FastAPI provides a robust and scalable backend for real-time question generation and user interaction.
Salah GPT is an Islamic assistant built using LangChain and FastAPI, leveraging large language models (LLMs) and natural language processing (NLP) techniques. The system uses LangChain's RAG capabilities for accurate Islamic knowledge retrieval and FastAPI for efficient API handling, providing real-time, context-aware responses to Islamic queries.
Healthcare Trends Analysis is a data-driven project focused on exploring and visualizing key trends in healthcare. Using advanced analytics and machine learning techniques, this project uncovers important insights related to healthcare costs, treatment efficacy, and the evolving needs of patients.
Hourly Energy Forecasting is a machine learning project that focuses on predicting hourly energy consumption using time series data. The model leverages machine learning algorithms like ARIMA and LSTM to provide accurate forecasts for energy consumption, helping utilities optimize their resource management.
A sophisticated Retrieval-Augmented Generation (RAG) system built with LangChain, designed to provide accurate and context-aware responses by combining document retrieval with large language models.
Comprehensive data science program covering statistical analysis, machine learning, and data visualization
Advanced machine learning algorithms, neural networks, and deep learning applications
DeepLearning.AI course on generative AI applications and implementation strategies
Foundational AWS cloud services and architecture principles