I will do data science web application for you
Financial data scientist
About this Gig
What this gig is: it is a data science web application, serving many purposes by using ML as backend, and libraries like streamlit as frontend and connecting both using FastAPI, to display numerous things, (Dashboards, graphs, metrics, and anything the customer asks for), the application is then deployed on the cloud of your choice,the backend ML code will be dockerized and pushed to the ECR, and will have connections with the storage section (eg, s3), and the secrets section (where your api key lives), the github action will be responsible for running daily inference and giving instructions to (Sagemaker/AWS Lambda) to output the extracted daily data plus predicitons to storage (s3), and the frontend will live in Cloud Run / AWS App Runner / Hugging Face, and displays the metrics / graphs 24/7 with minimal costs,
what is gig isn't: it is not meant for a full business end to end complex application, such application will require multiple machine learning models (forecasting, customer lifetime value, recommender systems), which in turn require more time to fine tune and connect together, and a sophisticated setup on the cloud, for such application i have other gigs focused on that
Programming language:
Python
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SQL
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NoSQL
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MLflow
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Amazon SageMaker
Frameworks:
Scikit-learn
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Panda
APIs:
Amazon Rekognition
Tools:
Jupyter Notebook
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MLflow
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Colab

