Machine-Learning-Deep-Learning

Assignment Chapter 2 - StartupCampus AI Batch 7

This repository contains the implementation and analysis of four cases provided in Assignment Chapter 2 for the StartupCampus AI Batch 7 program, focusing on Machine Learning and Deep Learning. Each case is developed using Python and the TensorFlow-Keras framework, covering various prediction and classification tasks.

Table of Contents

• Introduction
• Cases
  • Case 01: Classification
  • Case 02: Binary Classification
  • Case 03: Deep Learning Regression
  • Case 04: Object Detection
• Usage
• Requirements

Introduction

This assignment explores various Machine Learning and Deep Learning methods, including classification, regression, and object detection. Each case is implemented with a tailored approach to achieve optimal model performance, with the aim of meeting accuracy standards for each task.

Cases

Case 01: Classification

This case involves developing a multiclass classification model to categorize data based on available features. The model is optimized to minimize classification error.

Case Details:

• Type: Multiclass Classification
• Framework: TensorFlow-Keras
• Goal: Achieve optimal accuracy in multiclass classification

Case 02: Binary Classification

The second case focuses on binary classification, where the model predicts one of two possible classes. This approach is widely used in applications like spam detection and image classification.

Case Details:

• Type: Binary Classification
• Framework: TensorFlow-Keras
• Goal: Achieve optimal accuracy in binary prediction

Case 03: Deep Learning Regression

In the third case, a deep learning model is used for continuous value prediction, specifically for predicting house prices in California based on the provided dataset. The regression model is designed to minimize prediction error.

Case Details:

• Type: Regression
• Framework: TensorFlow-Keras
• Goal: Predict house prices with optimal accuracy
• Dataset: California Housing Prices

Case 04: Object Detection

The final case involves developing an object detection model to identify and locate specific objects in images.

Case Details:

• Type: Object Detection
• Framework: TensorFlow-Keras
• Goal: Detect and determine object positions in images

Usage

1. Clone this repository:

   git clone https://github.com/username/repository-name.git

2. Install the necessary dependencies:

   pip install -r requirements.txt

3. Run the corresponding notebook or script for each case.

Requirements

• Python 3.7 or higher
• TensorFlow 2.x
• Jupyter Notebook (for execution and results visualization)