Sentiment Analysis Project (SAP01)

This course teaches students how to use Excel for data analysis, helping them understand fundamental terminology, principles, and approaches used in working with data.

Course curriculum

1. 1.1 Introduction
2. 1.2 Understanding the Objective
3. 1.3 AI Project Steps
1. 2.1 Steps to Set up Your Environment
2. 2.2 Why We Need to Setup Our Environment
3. 2.3 Setting up Our Project Environment
1. 3.1 Steps for Loading a Pretrained Model
2. 3.2 Load & Test a Pretrained Model
1. 4.1 Why do We Need to Evaluate AI Models
2. 4.2 Loading Custom Data for Model Evaluation
3. 4.3 Creating a Function for Model Evaluation
4. 4.4 Get Predictions & Convert to Binary
5. 4.5 Accuracy Score & Classification Report
6. 4.6 Evaluating an AI Model for Improvements
1. 5.1 Interactive Testing an AI Model
1. 6.1 Build an AI Web App with Streamlit
1. 7.1 Add Proper Edge Cases
1. 8.1 Confusion Matrix Heatmap Evaluation
1. 9.1 Intro to Finetuning
2. 9.2 Collecting Data for Finetuning
3. 9.3 Fine Tuning our Model
4. 9.4 Testing our Model
1. 10.1 Creating a README
2. 10.2 Pushing to GitHub
3. 10.3 What is Next?
1. Course Feedback Form

About this course

26 lessons

ITonlinelearning Academy

Sentiment Analysis Project (SAP01)

Course curriculum

Module 1: Introduction

Module 2: Setting up the Environment

Module 3: Load Pretrained model

Module 4: Work with Real Data and Evaluate our Model

Module 5: Interactive Testing an AI Model

Module 6: Build an AI Web Application

Module 7: Discuss Other Considerations for AI Development

Module 8: Create a Visualisation to Evaluate our Model

Module 9: Fine Tuning an AI Model

Module 10: Wrapping Up The Project

Course Feedback

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