End To End Deep Learning Project | Euron

Опубликовано: 02 Февраль 2025
на канале: Euron

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Ready to dive into deep learning? 🚀 In this comprehensive tutorial, you'll learn how to build a deep learning pipeline from scratch! Perfect for beginners and advanced learners alike, this video walks you through every step—from data ingestion to deploying an image classification project using TensorFlow and MLOps tools.

🔑 What you'll learn:
How to create a deep learning pipeline for image classification.
Using pre-trained models like VGG16 and customizing them.
Step-by-step guidance on data preparation, model training, evaluation, and predictions.
Practical deployment with Docker, AWS, and CI/CD pipelines.
Tips for mastering MLOps tools and enhancing project scalability.

Whether you're just starting out or looking to refine your skills, this tutorial is packed with actionable insights. Hit play and code along to kickstart your deep learning journey today!

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#pytorch #datascienceproject #computervision #tensorflow #machinelearningprojects

CHAPTERS:
00:00 - Introduction
01:48 - Agenda Overview
04:46 - Problem Statement Analysis
06:50 - Creating GitHub Repository
08:20 - Project Template Setup
11:41 - Project Requirements Configuration
15:48 - Logger Exception Creation
19:54 - Understanding @staticmethod
25:50 - Exception Utility Development
26:11 - Project Workflow Explanation
27:32 - Data Injection Techniques
29:38 - Data Collection Methods
34:00 - Updating Configuration File
39:50 - Data Ingestion Process
46:00 - Preparing Base Model
46:30 - Image Classification with Transfer Learning
50:45 - Base Model Preparation
52:13 - Configuration Update
54:35 - Entity Creation
55:00 - Parameter Updates
55:08 - Config Manager Creation
59:10 - Converting Notebook to Modular Code
1:02:55 - Model Training Process
1:11:17 - Model Evaluation Techniques
1:17:54 - Creating Prediction Pipeline
1:19:35 - User Application Development
1:25:06 - Final Deployment Steps
1:27:27 - Copying Model to Directory
1:28:49 - Deployment Process Overview
1:31:25 - Understanding CI/CD Deployment
1:37:10 - Creating AWS Resources
1:38:05 - IAM User Creation
1:39:55 - ECR Repository Setup
1:40:37 - EC2 Instance Creation
1:44:07 - Configuring Self-Hosted Runner
1:45:51 - Connecting GitHub to AWS
1:46:26 - Adding Security Credentials
1:48:44 - CI/CD Pipeline Execution
1:50:05 - Testing Deployed Application
1:51:42 - Deleting AWS Resources
1:53:17 - Next Machine Learning Project
1:53:21 - Course Conclusion

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