Practical Computer Vision From Zero to Hero over 10 Topics

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Free Download Practical Computer Vision From Zero to Hero over 10 Topics
Published 11/2025
Created by Neuralearn Dot AI
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All | Genre: eLearning | Language: English | Duration: 49 Lectures ( 7h 35m ) | Size: 4.68 GB

Build AI Systems: Sports Analytics with YOLOv8, AI Interior Design with Stable Diffusion & Invoice Parsing with Llama 3
What you'll learn
Build an image classifier with Hugging Face Transformers and deploy it as a FastAPI.
Train a YOLOv8 model for real-time ball detection in images and videos.
Use Grounding DINO for zero-shot player detection without specific training.
Implement DeepSORT to track multiple players consistently throughout a video.
Project player and ball positions onto a 2D map using homography with OpenCV.
Train a YOLOv8-Pose model to detect custom key points on a tennis court.
Generate new interior designs from empty rooms using Stable Diffusion img2img.
Create realistic depth maps from single images with the Depth Anything model.
Produce precise object masks using Grounding DINO and the Segment Anything Model.
Control AI image generation with ControlNet using depth and segmentation maps.
Generate photorealistic influencer images with the advanced FLUX model.
Insert products seamlessly into AI-generated images using the InsertAnything framework.
Extract text from invoices and receipts automatically using PaddleOCR.
Train a Llama 3 model with Unsloth to parse and structure extracted OCR data.
Optimize model performance by converting models to ONNX for faster inference.
Fine-tune large language and vision models efficiently using LoRA adapters.
Deeploying Onnx models with fastapi
Requirements
Basic Python Programming Skills
Fundamentals of Machine Learning
Familiarity with Jupyter Notebooks or Google Colab
Introduction to Deep Learning & Neural Networks
Basic knowledge of computer vision concepts
Description
Are you ready to go beyond basic tutorials and build sophisticated, real-world AI systems? While many courses teach you how to classify an image, the real power of AI lies in creating complex, multi-model pipelines that solve challenging problems. This is where the industry is heading, and where the top-tier AI engineers operate.In fields like sports analytics, AI is revolutionizing how we understand the game by tracking players and projecting plays. In creative industries, generative AI is transforming empty rooms into stunning interior designs and creating photorealistic virtual influencers. In business, AI is automating the tedious task of parsing data from invoices and receipts.The demand for engineers who can build these advanced, integrated AI solutions is higher than ever. However, learning how to combine state-of-the-art models like YOLOv8, Grounding DINO, Stable Diffusion, and Llama 3 into a single, cohesive application is a skill that few courses teach.This is that course.In this comprehensive, project-based journey, we will take you from individual AI concepts to building complete, portfolio-worthy systems. You will learn not just the "how" but the "why," using cutting-edge libraries like Hugging Face, Ultralytics, and PyTorch. We won't just train a model; we will optimize it with ONNX, deploy it with FastAPI. We shall also learn how to fine-tune LLMs efficiently with LoRA and Unsloth.By the end of this course, you won't just be an AI practitioner; you will be an AI architect, capable of designing and implementing complex solutions that are at the forefront of technology.You will build incredible, real-world projects, including:An Automated Sports Analytics System that detects and tracks tennis players and the ball, projecting their movements onto a 2D court map.An AI Interior Designer that uses Stable Diffusion, ControlNet, segmentation and depth estimation to realistically furnish images of empty rooms.A Virtual Influencer Generator using the powerful FLUX model to create lifelike people and seamlessly place products in their hands with InsertAnything.An Intelligent Document Processor that uses OCR to extract text from invoices and a custom-trained Llama 3 model to parse it into structured data.If you are ready to elevate your career and build the kind of AI applications that define the future, this course is your definitive guide. We are incredibly excited to help you achieve your goals!This course is offered to you by Neuralearn. We are committed to your success. Your feedback and questions in the forum are vital, and we will be there to support you every step of the way.Let's start building
Who this course is for
Software Developers & Engineers
Aspiring AI & Machine Learning Engineers
Tech Enthusiasts & Hobbyists
Entrepreneurs & Product Managers
Graduate Students & Researchers
Homepage
https://www.udemy.com/course/practical-c...10-topics/

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