Tutorial covers: Deploying a Sentiment Analysis Python App using PIP & Virtual Environment in Flask. You may run this project on your end using our Project GitHub Repo.
This is part-2 of our Sentiment Analysis Project series, in which we are covering the entire ML project journey of: formulating a problem, training ML model, deploying & then testing it in a live environment. In this part-2, we are deploying a Machine Learning Model in Flask using PIP & Virtualenv.
Model Building (part-1) of this series is here: • Sentiment Analysis Machine Learning P...
We have used Scikit-learn Pipeline for model building, which is a low code magical way of building models.
Happy learning to you! :)
🔥 Sections:
00:00 Introduction & ML Basics
02:45 Plan of Action
06:48 Creating Front-end (HTML Page)
09:00 Creating Back-end (Flask App)
10.58 Virtual Environment
17:38 Running Model in Live Environment
19:26 Container Packaging
24:58 Basics of GitHub
🔥 Resources:
Model Building (Phase-1) of this End-to-End Project: • Sentiment Analysis Machine Learning P...
GitHub Repo Link: https://github.com/skillcate/sentimen...
Google Drive Link: https://drive.google.com/drive/folder...
Sentiment Analysis Project based Review Classification Project from Skillcate: • Sentiment Analysis Project using Mach...
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Facebook: / mlprojects
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