YOLO-V3 using Darknet Framework On NVIDIA GPU Without Coding

This is course having 3 Basic things one is Deep learning RIG, second is NVIDIA GPU, Third is UBUNTU 18.04 LTS OS
3.92 (18 reviews)
Udemy
platform
English
language
Data Science
category
YOLO-V3 using Darknet Framework On NVIDIA GPU Without Coding
140
students
3 hours
content
Dec 2019
last update
$29.99
regular price

Why take this course?


Master YOLO-v3 with Darknet on NVIDIA GPU: A Hands-On Deep Learning Adventure 🧠🚀

Welcome to the Ultimate Deep Learning Practical Course!

Are you ready to dive into the world of real-time object detection with YOLO-v3 (You Only Look Once) using the Darknet Framework? This comprehensive course is designed for students and professionals who want to harness the power of NVIDIA GPUs and Ubuntu 18.04 LTS to implement state-of-the-art object detection models without the need for extensive coding knowledge.

Course Overview:

In this course, you will:

  • Understand the Core Concepts: Gain a solid grasp of deep learning with hands-on experience using the pre-trained YOLOv3 model.
  • Leverage NVIDIA GPU Power: Utilize the latest NVIDIA GPUs to speed up your training and inference processes, enabling you to handle complex models with ease.
  • Master Ubuntu 18.04 LTS: Learn to navigate and configure one of the most popular and robust operating systems for machine learning and AI applications.

Why Enroll in This Course?

🎓 Practical Skills for Real-World Applications: This course is tailored for immediate practical application, ideal for students and professionals working on their dissertations or projects in computer vision and object detection.

  • Deep Learning with RIG (Research, Innovation, and Growth): Engage with advanced deep learning concepts that are shaping the future of AI.
  • Hands-On NVIDIA GPU Experience: Learn to harness the computational power of NVIDIA GPUs for real-time object detection tasks.
  • Ubuntu 18.04 LTS Mastery: Become proficient in using this OS, which is a staple in the tech industry for its performance and stability.

Course Structure:

  • Introduction to YOLO-v3 and Darknet Framework: Understand the architecture and capabilities of YOLO-v3.
  • Setting Up Your Environment: Install Darknet and configure your NVIDIA GPU and Ubuntu 18.04 LTS for optimal performance.
  • Custom Object Detection: Learn how to train YOLO-v3 to detect custom objects in images and videos.
  • Project Implementation: Work on a capstone project where you will implement everything learned throughout the course, from setting up your environment to training the model for custom object detection.

Course Benefits:

  • 🚀 Boost Your Career: Stand out in the job market by mastering one of the most powerful object detection models and frameworks.
  • 🤝 Community Support: Join a community of like-minded learners and experts who are passionate about AI and machine learning.
  • Learn From an Expert: Be guided by instructor Dhavalshree Khedkarc, whose expertise will ensure you get the most out of this course.

Prerequisites:

  • Basic understanding of Python programming.
  • Familiarity with machine learning concepts.
  • A computer with NVIDIA GPU and Ubuntu 18.04 LTS installed.

Ready to unlock the potential of YOLO-v3 using Darknet on your NVIDIA GPU? Enroll now and transform your understanding of deep learning and object detection! 🌟


Course Outline:

  1. Introduction to Deep Learning with YOLO-v3: An overview of the YOLO (You Only Look Once) algorithm and its evolution into YOLO-v3.
  2. Setting Up Your Development Environment: Step-by-step guide to installing Darknet, NVIDIA drivers, CUDA toolkit, and cuDNN on Ubuntu 18.04 LTS.
  3. Understanding the Darknet Framework: Dive into the inner workings of the Darknet framework, its advantages, and how it's different from other deep learning frameworks.
  4. Data Collection and Annotation for Custom Object Detection: Techniques for gathering and annotating your data efficiently.
  5. Training YOLO-v3 Model with Custom Datasets: Learn the process of training YOLO-v3 on your own dataset from scratch.
  6. Optimizing Model Performance: Tips and tricks to fine-tune your model to achieve the best accuracy and speed.
  7. Practical Capstone Project: Apply all the concepts learned in a comprehensive project that showcases your newfound expertise in YOLO-v3 using Darknet on NVIDIA GPU.

Join us now and be at the forefront of AI technology with YOLO-v3 using Darknet on NVIDIA GPUs! 🤖✨


Enroll today and take the first step towards becoming an expert in real-time object detection with YOLO-v3 using the Darknet Framework on NVIDIA GPUs. Let's embark on this journey to revolutionize your approach to AI and machine learning! 🎓🚀

Course Gallery

YOLO-V3 using Darknet Framework On NVIDIA GPU Without Coding – Screenshot 1
Screenshot 1YOLO-V3 using Darknet Framework On NVIDIA GPU Without Coding
YOLO-V3 using Darknet Framework On NVIDIA GPU Without Coding – Screenshot 2
Screenshot 2YOLO-V3 using Darknet Framework On NVIDIA GPU Without Coding
YOLO-V3 using Darknet Framework On NVIDIA GPU Without Coding – Screenshot 3
Screenshot 3YOLO-V3 using Darknet Framework On NVIDIA GPU Without Coding
YOLO-V3 using Darknet Framework On NVIDIA GPU Without Coding – Screenshot 4
Screenshot 4YOLO-V3 using Darknet Framework On NVIDIA GPU Without Coding

Loading charts...

2696526
udemy ID
09/12/2019
course created date
13/09/2020
course indexed date
Bot
course submited by