I am a Python Developer and Machine Learning Engineer with over 2 years of experience in building complex AI, ML, and web applications. Skilled at writing clear, concise code that is easy to maintain and troubleshoot. I am well-versed in Machine Learning, Python Web Framework Django, JavaScript, and Software Development. My areas of expertise are data analysis, machine learning, deep learning, web scraping, and web application development.
0 + Projects completed
Seasoned Python Developer with over 2 years of hands-on experience in AI/ML, web applications, and backend systems. Proven expertise in data science, machine learning algorithms, and web development.
➢I've contributed to Serenus One, a startup focused on building a personalized meditation platform. My work involves developing robust Django REST API and FastAPI solutions for key features, including user authentication, integration of Google and Discord login systems, implementation of payment and subscription models, and development of a text-to-speech (TTS) system (open source models - piper tts, coqui tts etc.) for generating meditation scripts and fine tuning of OpenAI models gpt-4o.
➢ I am working on the Enny Sports mobile application, developing the Django REST API for its Flutter-based iOS and Android apps, with its prototype beta version available on AppStore and PlayStore. Enny Sports is the ultimate fitness app, uniting sports enthusiasts on iOS and Android, connecting individuals interested in various sports and fitness activities. Users can find certified personal trainers and participate in courses offered by different trainers.
Here, I worked on the "Inventory Management System" Django web-based application for Rana Motors, which allowed me to gain valuable insights into web development and database management.
➢Here,I've worked on an e-commerce web application, with an emphasis on building reliable back-end APIs using the Django Rest Framework for seamless functionality and performance.
➢Here, I've worked on the Music Classification with Deep Learning project of Pixalytix. The project goal is to classify music based on various attributes such as genre, tempo, mood, vocal type, language, and more using deep learning models. I will implement both CNN and LSTM to achieve accurate classification across these multiple dimensions.
As a Machine Learning Engineer at Engineer Hut, I was responsible for collecting, preprocessing, and analyzing large datasets to train and optimize deep learning models. I developed and implemented machine learning and deep learning models, collaborating with teams to gather and analyze data for model training and evaluation.
Below are some of the AI, ML, and web projects I have worked on.
Developed a backend API for an e-commerce platform using Django Rest Framework, including authentication, product management, cart, and order handling.
Developed a web app for crop disease prediction using Transfer Learning models like InceptionV3 and MobileNetV2.
Built a book recommendation system using KNN, LightFM, and Cosine Similarity, with results displayed in a Streamlit app.
Developed a chatbot utilizing OpenAI's LLM, Langchain, and VectorDB for efficient Q&A functionalities.
Created a chatbot to analyze PDF documents using OpenAI's language models and VectorDB for data extraction.
Designed an AI-powered resume tracking system to analyze resumes and track candidates' applications efficiently.
Implemented machine learning models such as ARIMA, LSTM, and GRU to predict stock market prices.
Built machine learning models to predict water quality using Random Forest, Decision Tree, XGBoost, and LightGBM.
Created ML models to predict breast cancer using multiple algorithms for high accuracy.
Implemented a CNN model to classify ball images with optimized accuracy and performance.
Built an LSTM-based model for recognizing emotions in speech using NLP techniques.
Below are the details to reach out to me!
Dhaka, Bangladesh