Complete Deep Learning Projects In Python From Scratch - Printable Version +- Softwarez.Info - Software's World! (https://softwarez.info) +-- Forum: Library Zone (https://softwarez.info/Forum-Library-Zone) +--- Forum: Video Tutorials (https://softwarez.info/Forum-Video-Tutorials) +--- Thread: Complete Deep Learning Projects In Python From Scratch (/Thread-Complete-Deep-Learning-Projects-In-Python-From-Scratch--323226) |
Complete Deep Learning Projects In Python From Scratch - BaDshaH - 01-13-2024 Published 1/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 1.96 GB | Duration: 1h 44m Learn Complete Deep Learning Projects In Python From Scratch [b]What you'll learn[/b] Explore the process of collecting and preprocessing datasets of facial expressions, ensuring the data is optimized for training a YOLOv7 model. Dive into the annotation process, marking facial expressions on images to train the YOLOv7 model for accurate and robust emotion detection. Explore the end-to-end training workflow of YOLOv7 using the annotated and preprocessed dataset, adjusting parameters and monitoring model performance. Understand how to deploy the trained YOLOv7 model for real-world emotion detection tasks, making it ready for integration into applications or systems. [b]Requirements[/b] Basic understanding of machine learning concepts. Access to a computer with internet connectivity. [b]Description[/b] Course Title: Learn Complete Deep Learning Projects In Python From ScratchCourse Description:Welcome to the comprehensive course on "Learn Complete Deep Learning Projects In Python From Scratch using Roboflow." This course is designed to provide students, developers, and healthcare enthusiasts with hands-on experience in implementing the YOLOv8 object detection algorithm for the critical task of detecting brain tumors in MRI images. Through a complete project workflow, you will learn the essential steps from data preprocessing to model deployment, leveraging the capabilities of Roboflow for efficient dataset management.What You Will Learn:Introduction to Medical Imaging and Object Detection:Gain insights into the crucial role of medical imaging, specifically MRI, in detecting brain tumors. Understand the fundamentals of object detection and its application in healthcare using YOLOv8.Setting Up the Project Environment:Learn how to set up the project environment, including the installation of necessary tools and libraries for implementing YOLOv8 for brain tumor detection.Data Collection and Preprocessing:Explore the process of collecting and preprocessing MRI images, ensuring the dataset is optimized for training a YOLOv8 model.Annotation of MRI Imagesive into the annotation process, marking regions of interest (ROIs) on MRI images to train the YOLOv8 model for accurate and precise detection of brain tumors.Integration with Roboflow:Understand how to seamlessly integrate Roboflow into the project workflow, leveraging its features for efficient dataset management, augmentation, and optimization.Training YOLOv8 Model:Explore the complete training workflow of YOLOv8 using the annotated and preprocessed MRI dataset, understanding parameters, and monitoring model performance.Model Evaluation and Fine-Tuning:Learn techniques for evaluating the trained model, fine-tuning parameters for optimal performance, and ensuring accurate detection of brain tumors in MRI images.Deployment of the Model:Understand how to deploy the trained YOLOv8 model for real-world brain tumor detection tasks, making it ready for integration into a medical environment. Overview Section 1: Introduction To Complete Deep Learning Projects In Python From Scratch Lecture 1 Introduction To Brain Tumor Detection Using YOLOv8 Project Lecture 2 PROJECT CREATION Lecture 3 DATASET CREATION FOR BRAIN TUMOR DETECTION Lecture 4 ANNOTATION FOR DATASET Lecture 5 TRAINING DATASET WITH YOLOV8 MODEL Lecture 6 VALIDATE MODEL Lecture 7 PROJECT EXECUTE IN PYCHARM IDE Section 2: INTRODUCTION TO EMOTION DETECTION USING YOLOv7 PROJECT Lecture 8 INTRO TO PROJECT Lecture 9 ACCOUNT CREATION Lecture 10 DATASET CREATION Lecture 11 ANNOTATION AND LABELLING Lecture 12 TRAIN YOLOV7 MODEL Lecture 13 VALIDATE YOLOV7 MODEL Lecture 14 PROJECT EXECUTION IN PYCHARM Section 3: INTRODUCTION TO FACE RECOGNITION USING YOLOv7 PROJECT Lecture 15 INTRO TO PROJECT Lecture 16 PROJECT CREATION Lecture 17 DATASET CREATION USING VIDEOS AND IMAGES Lecture 18 ANNOTATION FOR DATASET Lecture 19 TRAIN YOLOV7 MODEL Lecture 20 VALIDATE YOLOV7 MODEL Lecture 21 PROJECT EXECUTE IN PYCHARM Section 4: INTRODUCTION TO GOOGLE COLAB Lecture 22 INTRO TO COLAB Lecture 23 IMPORT PROJECT Lecture 24 TRAIN MODEL IN COLAB Lecture 25 VALIADATE MODEL IN COLAB Lecture 26 DOWNLOAD MODEL IN COLAB Students and professionals in the field of medical imaging and artificial intelligence.,Developers and data scientists interested in applying YOLOv8 for medical object detection projects. Homepage |