Build & Deploy Machine Learning Models for Data-Driven Solutions by Sneha Das KarmakarBuild & Deploy Machine Learning Models for Data-Driven Solutions by Sneha Das Karmakar

Build & Deploy Machine Learning Models for Data-Driven Solutions

Sneha Das Karmakar

Starting at

About this service

Summary

I offer end-to-end machine learning solutions, from understanding business problems and data preprocessing to developing optimized models and deploying them to Azure. What sets me apart is my comprehensive approach, providing well-documented code in VS Code Jupyter Notebooks, and delivering a seamless integration of machine learning models that align with client requirements for real-time applications and easy access through GitHub

What's included

Business Understanding, Data Collection, Preprocessing, and Model Development
Understand the business problem, collect raw data, preprocess it (handling missing values, outliers, scaling), and develop a suitable machine learning model. The model will undergo hyperparameter tuning for optimization, followed by comprehensive evaluation to ensure accuracy and reliability. Format: Python scripts, VS Code, Jupyter Notebook (.ipynb), model files (.pkl)
Code Delivery on GitHub
Deliver all project code on GitHub, including well-documented scripts and notebooks, enabling the client to access, modify, and manage the code efficiently. Format: GitHub repository link, including code in VS Code
Azure Deployment Based on Client Requirements
Deploy the trained machine learning model to Azure, ensuring it aligns with the client’s infrastructure and operational requirements for real-time or batch predictions. Format: Azure deployment setup

Duration

4 weeks

Skills and tools

ML Engineer

AI Model Developer

AI Developer

Jupyter

Python

Visual Studio Code

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