Build & Deploy AI/ML Web Apps: Hands-On Tutorial (Streamlit,GitHub, API)

Publié le: 08 juin 2025
sur la chaîne: Tony Tech Insights

157

👨‍🏫 In this hands-on machine learning session, Dr. Onoja guides students through the complete end-to-end workflow of deploying an ML model using Python — from training in Jupyter Notebook to publishing on Streamlit Cloud.

🧠 What You’ll Learn:
0:00 – 7:00 | How to train a Random Forest classifier on the Iris dataset

8:00 – 24:00 | How to use Generative AI (e.g., ChatGPT/Copilot) to write production-ready Python scripts

31:00 – 47:20 | How to upload your project to a GitHub repository

47:20 – 49:50 | How to deploy a fully functional Streamlit app to the web

🎯 Key Skills Practiced:
Model training & evaluation

Serialization with Joblib

Prompting GenAI for boilerplate code

GitHub repository creation & commit workflow

Model deployment using Streamlit cloud

🧰 Tools Used:
Python, Jupyter Notebook, scikit-learn, Streamlit, GitHub, Generative AI (ChatGPT/Copilot)

📦 Dataset:
The classic Iris dataset — ideal for demonstrating classification tasks.

📍 Recorded live during a DataEdge Academy class session on model deployment.
📌 Whether you're a data science student or an aspiring ML engineer, this session offers real-world exposure to production-ready workflows.

🌐 Helpful Links:
Github repo: https://github.com/Donmaston09/explai...
🔗 Streamlit: https://streamlit.io/
🚀 Live App: Deployed Iris Classifier

🔗 Connect:
📧 Email: donmaston09@gmail.com
📺 YouTube: @tonyonoja7880
🌐 Facebook: DataEdge Academy

👍 Don’t forget to Like, Subscribe, and Comment if you found this helpful!

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