【評判】Machine Learning Deep Learning Model Deployment

Machine Learning Deep Learning Model Deployment techniques
Simple Model building with Scikit-Learn , TensorFlow and PyTorch
Deploying Machine Learning Models on cloud instances
TensorFlow Serving and extracting weights from PyTorch Models
Creating Serverless REST API for Machine Learning models
Deploying tf-idf and text classifier models for Twitter sentiment analysis
Deploying models using TensorFlow js and JavaScript
Machine Learning experiment and deployment using MLflow
Agent-Mode Model Building and Deployment with GitHub Copilot

In this course you will learn how to deploy Machine Learning Deep Learning Models using various techniques.  This course takes you beyond model development and explains how the model can be consumed by different applications with hands-on examples

Course Structure:

1. Creating a Classification Model using Scikit-learn

2. Saving the Model and the standard Scaler

3. Exporting the Model to another environment - Local and Google Colab

4. Creating a REST API using Python Flask and using it locally

5. Creating a Machine Learning REST API on a Cloud virtual server

6. Creating a Serverless Machine Learning REST API using Cloud Functions

7. Building and Deploying TensorFlow and Keras models using TensorFlow Serving

8. Building and Deploying  PyTorch Models

9. Converting a PyTorch model to TensorFlow format using ONNX

10. Creating REST API for Pytorch and TensorFlow Models

11. Deploying tf-idf and text classifier models for Twitter sentiment analysis

12. Deploying models using TensorFlow.js and JavaScript

13. Tracking Model training experiments and deployment with MLFLow

14. Running MLFlow on Colab and Databricks

    
    

Appendix - Generative AI - Miscellaneous Topics.

• OpenAI and the history of GPT models

• Creating an OpenAI account and invoking a text-to-speech model from Python code

• Invoking OpenAI Chat Completion, Text Generation, Image Generation models from Python code

• Creating a Chatbot with OpenAI API and ChatGPT Model using Python on Google Colab

• ChatGPT, Large Language Models (LLM) and prompt engineering

New Section : Agent-Mode Model Building and Deployment with GitHub Copilot

• Vibe Coding: Model Development with GitHub Copilot Using a Single Prompt

• Building a REST API for ML Model with a Simple Prompt Using GitHub Copilot

• Building Interactive ML Web Apps with Copilot in Agent Mode

• Creating a Serverless Machine Learning API with AWS S3, Lambda, and API Gateway

This course is designed for beginners with no prior experience in Machine Learning or Deep Learning. A basic background in Python is required.

You will also learn how to build and deploy a Neural Network using TensorFlow Keras and PyTorch. Google Cloud (GCP) free trial account is required to try out some of the labs designed for cloud environment.

This course uses high-quality AI-generated text-to-speech narration to complement the powerful visuals and enhance your learning experience.