riversongs Posted January 12, 2024 Report Share Posted January 12, 2024 Free Download Complete Deep Learning Projects In Python From ScratchPublished 1/2024MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHzLanguage: English | Size: 1.96 GB | Duration: 1h 44mLearn Complete Deep Learning Projects In Python From ScratchWhat you'll learnExplore 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.RequirementsBasic understanding of machine learning concepts.Access to a computer with internet connectivity.DescriptionCourse 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 Images:Dive 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.OverviewSection 1: Introduction To Complete Deep Learning Projects In Python From ScratchLecture 1 Introduction To Brain Tumor Detection Using YOLOv8 ProjectLecture 2 PROJECT CREATIONLecture 3 DATASET CREATION FOR BRAIN TUMOR DETECTIONLecture 4 ANNOTATION FOR DATASETLecture 5 TRAINING DATASET WITH YOLOV8 MODELLecture 6 VALIDATE MODELLecture 7 PROJECT EXECUTE IN PYCHARM IDESection 2: INTRODUCTION TO EMOTION DETECTION USING YOLOv7 PROJECTLecture 8 INTRO TO PROJECTLecture 9 ACCOUNT CREATIONLecture 10 DATASET CREATIONLecture 11 ANNOTATION AND LABELLINGLecture 12 TRAIN YOLOV7 MODELLecture 13 VALIDATE YOLOV7 MODELLecture 14 PROJECT EXECUTION IN PYCHARMSection 3: INTRODUCTION TO FACE RECOGNITION USING YOLOv7 PROJECTLecture 15 INTRO TO PROJECTLecture 16 PROJECT CREATIONLecture 17 DATASET CREATION USING VIDEOS AND IMAGESLecture 18 ANNOTATION FOR DATASETLecture 19 TRAIN YOLOV7 MODELLecture 20 VALIDATE YOLOV7 MODELLecture 21 PROJECT EXECUTE IN PYCHARMSection 4: INTRODUCTION TO GOOGLE COLABLecture 22 INTRO TO COLABLecture 23 IMPORT PROJECTLecture 24 TRAIN MODEL IN COLABLecture 25 VALIADATE MODEL IN COLABLecture 26 DOWNLOAD MODEL IN COLABStudents and professionals in the field of medical imaging and artificial intelligence.,Developers and data scientists interested in applying YOLOv8 for medical object detection projects.Homepagehttps://www.udemy.com/course/complete-deep-learning-projects-in-python-from-scratch/Download ( Rapidgator )https://rg.to/file/121d77c448c0148f696a42f1cd3b008c/ynead.Complete.Deep.Learning.Projects.In.Python.From.Scratch.part1.rar.htmlhttps://rg.to/file/055d5a4286a2a7c9147867f490861546/ynead.Complete.Deep.Learning.Projects.In.Python.From.Scratch.part2.rar.htmlhttps://rg.to/file/e0527f727317bac61bfc69fdf0efd069/ynead.Complete.Deep.Learning.Projects.In.Python.From.Scratch.part3.rar.htmlUploadgighttps://uploadgig.com/file/download/d8565f2C9a7745Ab/ynead.Complete.Deep.Learning.Projects.In.Python.From.Scratch.part1.rarhttps://uploadgig.com/file/download/4b44f5f0DfFa2890/ynead.Complete.Deep.Learning.Projects.In.Python.From.Scratch.part2.rarhttps://uploadgig.com/file/download/9b7f15d65bDb5d68/ynead.Complete.Deep.Learning.Projects.In.Python.From.Scratch.part3.rarDownload ( NitroFlare )https://nitroflare.com/view/D525DB808E9BC57/ynead.Complete.Deep.Learning.Projects.In.Python.From.Scratch.part1.rarhttps://nitroflare.com/view/475E1E57F50770B/ynead.Complete.Deep.Learning.Projects.In.Python.From.Scratch.part2.rarhttps://nitroflare.com/view/D399B8DB4E276A9/ynead.Complete.Deep.Learning.Projects.In.Python.From.Scratch.part3.rarFikperhttps://fikper.com/dyNpAc0jnA/ynead.Complete.Deep.Learning.Projects.In.Python.From.Scratch.part1.rar.htmlhttps://fikper.com/i6dGfQwUJZ/ynead.Complete.Deep.Learning.Projects.In.Python.From.Scratch.part2.rar.htmlhttps://fikper.com/vpHRVkX05b/ynead.Complete.Deep.Learning.Projects.In.Python.From.Scratch.part3.rar.htmlNo Password - Links are Interchangeable Link to comment Share on other sites More sharing options...
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