Surat Banerjee

Surat Banerjee

Data Scientist / AI-ML Engineer
India
Bengali, Hindi, English

نبذة عني

As a data scientist with over 2.6+ years of experience within the industry, I have developed end-to-end Machine Learning and Deep Learning solutions across multiple domains. My standout contributions include Machine Lear…

الخبرة

Data Scientist

Freelance
Jan 2024 - Jun 2024 · 5 أشهر

• Developed a Chatbot with Multiple AI Documents. (more)
Objectives: It is an RAG-based LLM project with a Q&A chatbot.
Model: Llama3, Groq Inference, FAISS Vector DataBase, Streamlit, Python.
• Built Bottle_Counting_Detection, an AI-driven real-time object detection project. (more)
Objectives: For real-time detecting and tracking of bottles in the packaging domain.
Model: YoloV8, Deep Sort, Python.
• Created Code-Assistant-App. (more)
Objectives: The LLM project is to code an assistant app.
Model: CodeLlama, Streamlit, Python.
• Developed Nutritionist ChatBot deployment on HuggingFace. (more)
Objectives: The LLM project is to create a Q&A chatbot.
Model: Gemini-1.5-Pro, Streamlit, HuggingFace, Python.
• Implement a Chatbot with Multiple Documents. (more)
Objectives: It is a RAG based LLM project with a Q&A chatbot.
Model: Gemini-1.5-Pro, FAISS Vector DataBase, Gradio, Python.
• Built QA chatbot with deployment on HuggingFace. (more)
Objectives: The LLM project is to create a Q&A chatbot.
Model: Gemini-1.5-Pro, Streamlit, HuggingFace, Python.
• Implemented Vehicles Count Detection, an AI-driven real-time object detection project. (more)
Objectives: To use the YOLOv8 model for real-time, speed-based car detection.
Model: YoloV8, Deep Sort, Python
• Developed Tennis Player Detection, an AI-driven real-time object detection project. (more)
Objectives: For real-time player detection.
Model: YoloV8, Deep Sort, Python.

Data Scientist

DS Group
Apr 2022 - Nov 2023 · 1 سنة 7 أشهر

• Developed Bandwidth Prediction, a Machine Learning project.
Objectives: To forecast future bandwidth.
Model: Random Forest, Multiple linear regression.
• Implemented Stock price prediction, a machine learning project. (more)
Objectives: Predict stock prices using time series analysis.
Model: Long Short-Term Memory (LSTM).
• Built IPD - Insect-Pest-Detection, an AI-based object detection system. (more)
Objectives: To detect and track insects in real-time, and detection images with time send through email to pest controller.
Model: YoloV5, Deep Sort, Python.
• Created TSNA Leaf Classify, an AI-driven real-time object detection project. (more)
Objectives: To the classification and real-time detection of tobacco-specific nitro compounds in leaves (TSNAs).
Model: customized CNN model, YoloV5, Deep Sort, Python.
• Developed Supari Classify, an AI-based real-time object detection project. (more)
Objectives: The model will be used for real-time Supari classification and detection.
Model: YoloV8, Deep Sort, Python.

Data Scientist

Freelancer

Developed a Chatbot with Multiple AI Documents.
Built Bottle_Counting_Detection, an AI-driven real-time object detection project.
Created Code-Assistant-App.
Developed Nutritionist ChatBot deployment on HuggingFace.
Implemented a Chatbot with Multiple Documents.
Built QA chatbot with deployment on HuggingFace.
Implemented Vehicles Count Detection, an AI-driven real-time object detection project.
Developed Tennis Player Detection, an AI-driven real-time object detection project.

Data Scientist Trainee

ExcelDots

Developed E2E-GW-MySQL, a machine-learning project.

Data Science Intern

Artivatic.AI

Developed end-to-end machine learning projects, E2E-Flight-House utilizing Random Forest models with Flask integration.
Built end-to-end machine learning projects, E2E-Movie-Heart, utilizing Naive Bayes models with Flask integration.
Implemented an end-to-end deep learning project, E2E-HandWrittenDigit, using a custom CNN model within a Flask environment.

Data Science Intern

Lets Grow More

Delivered an end-to-end machine learning project, E2E-Diabetes-Spamham, and implemented Random Forest and Naive Bayes models utilizing Flask for project integration.

Full Stack Developer

Famocom Technology Pvt. Ltd.

Developed CRUD based applications using Angular, Spring Boot, Hibernate, and MySQL.

المهارات

ماي إس كيو إل بايثون (لغة برمجة) الرؤية الحاسوبية فلاسك (إطار عمل لتطبيقات الويب باستخدام Python) خوارزميات تعلم الآلة التعلم العميق NLP LangChain LLM OpenAI LLAMA Gemini Object Detection OpenCV Keras TensorFlow PyTorch ANN CNN RNN LSTM Neural Networks NumPy Pandas Scikit-Learn Machine Learning Classification Regression Time Series Analysis PowerBI AWS Azure HTML CSS Bootstrap Streamlit FAISS Groq YOLOv8 Deep SORT HuggingFace Gradio YOLOv5 Random Forest Multiple Linear Regression Lasso Regression Elastic Net Regression Naive Bayes Angular Spring Boot
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