Computer Vision Fundamentals

Master convolutional neural networks and modern computer vision architectures for image classification and object detection.

For those with an intermediate to advanced understanding of computer vision, this course covers advanced topics like deep learning, convolutional neural networks (CNNs), object detection, image segmentation, and generative models. It is taught by a renowned expert in the field and is designed for students with a strong programming background.

This course includes a module on Ensemble Learning, covering decision trees and random forests.

This course provides a comprehensive introduction to computer vision, covering topics like image processing, object detection, and the application of deep learning models in vision systems.

This beginner-level course introduces the exciting field of Computer Vision and its applications in various industries. You will learn about computer vision, its applications, and how to process images using Python, Watson AI, and OpenCV. The course also covers building image classification models and custom classifiers.

In this course, you will learn to track objects and detect motion in videos. You'll use pre-trained deep neural networks for object detection and optical flow for motion detection. The course project involves tracking cars on a busy highway.

Learn to use Power Query in Excel for data extraction, transformation, and loading, which are essential skills for data cleaning.

Learn about Computer Vision, one of the most exciting fields in Machine Learning, Artificial Intelligence and Computer Science.

Master Computer Vision and Deep Learning with Python and OpenCV Unlock the power of AI and machine learning to build intelligent computer vision applications.This comprehensive course will equip you with the skills to:Master Python Programming: Gain a solid foundation in Python programming, essential for data analysis, visualization, and machine learning.Harness the Power of OpenCV: Learn to process images and videos using OpenCV, a powerful computer vision library.Dive into Deep Learning: Explore state-of-the-art deep learning techniques, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial networks (GANs).Build Real-World Applications: Apply your knowledge to practical projects, such as:Object Detection and Tracking: Identify and track objects in real-time videos.Image Classification: Categorize images into different classes.Image Segmentation: Segment objects of interest from background images.Facial Recognition: Recognize and identify individuals from facial images.Medical Image Analysis: Analyze medical images to detect diseases.Autonomous Vehicles: Develop self-driving car technology, object detection, and lane detection.Retail: Customer analytics, inventory management, and security surveillance.Security and Surveillance: Facial recognition, object tracking, and anomaly detection.Leverage Advanced Techniques: Learn advanced techniques like transfer learning, fine-tuning, and model optimization to build high-performance models.Explore Cutting-Edge Topi

This course is designed for anyone interested in pursuing a career in artificial intelligence and computer vision or looking to implement computer vision applications in their projects. In "Computer Vision Smart Systems: Python, YOLO, and OpenCV -1," we start with the fundamentals of computer vision and cover image processing techniques using the Python programming language and OpenCV library. Then, we advance to object detection and deep learning modeling using the YOLO (You Only Look Once) algorithm. Students will learn to build custom deep learning models from scratch, work with datasets, perform object detection, and apply these models in various projects.Throughout the course, practical exercises are provided step-by-step along with theoretical knowledge, giving students the chance to apply what they've learned. Additionally, we address common challenges you may face and provide detailed solutions. Aimed at building skills from basic to intermediate levels, this course serves as a comprehensive guide for anyone interested in the field of computer vision. It empowers you to develop smart systems for your projects and enhances your expertise in this exciting domain."You are never too old to set another goal or to dream a new dream." - C.S.Lewis"Do the difficult things while they are easy and do the great things while they are small. A journey of a thousand miles begins with a single step" - Lao Tzu You get the best information that I have compiled over years of trial and error and experience!Best wishes,Yılmaz ALACA

Welcome to "AI 4 Everyone: Build Generative AI & Computer Vision Apps"—a comprehensive course designed for anyone looking to unlock the power of AI, whether you are a non-technical professional, or an aspiring AI developer.In this course, you’ll learn how to automate tasks, create powerful applications, and interact with AI models without needing extensive coding knowledge. Even if you’re a beginner, this course will guide you through building practical AI tools that simplify your day-to-day work.What You Will Learn:Automating Tasks with AI: Learn how to write professional emails, summarize You Tube videos, create stunning images, and explain complex graphs—all without writing a single line of code.Developing AI-Powered Applications: Using Python and Streamlit, you’ll create real-world applications like:A Recipe Generator that creates recipes based on your requests.An AI Meal Planner that organizes your meals based on nutritional needs.A You Tube Video to Blog Converter that transforms videos into blog posts.A PDF Sorter to efficiently organize and categorize documents.Document & Database Interactions: Discover how to chat with and extract information from documents, including:Text-to-SQL LLM Applications that query SQL databases.Multi-language Invoice Extractor that extracts text from invoices in various languages.PDF Q&A and sorting: Interact with your PDF files and manage them without the need for training or fine-tuning Large Language Models.LangChain Agents for CSV & JSON: Learn advanced AI techniques, like using LangChain agents to interact with CSV and JSON files for Q&A purp

Imagina crear, en pocos días, una inteligencia artificial que detecte tumores o enseñe a una consola Atari a batir récords, sin ser experto en matemáticas. El secreto está en proyectos guiados paso a paso, esto disparará tu motivación y retención.¿Qué vas a conseguir?Dominar Deep Learning e IA con TensorFlow desde cero, usando explicaciones que cualquier principiante puede entender a la primera.Construir 10 proyectos reales: detector de tumores, diagnóstico Covid con Transfer Learning, agente Atari autónomo, detector de violencia en vídeo y más, para impresionar a reclutadores con tu portafolio de proyectos de Inteligencia Artificial.Aprender con metodología 100 % práctica, probada para multiplicar la retención hasta 15 veces frente a clases teóricas con presentaciones aburridas.¿Por qué te importa?Empresas  buscan talento en IA más que nunca: las vacantes que piden TensorFlow crecieron un 34 % en el último año y pagan hasta un 25 % más que la media STEM. Además, la tecnología de redes neuronales ya supera a radiólogos en ciertas tareas de diagnóstico, de modo que estas habilidades abren puertas que transforman carreras y cambian vidas.Requisitos Solo Python básico y ganas de experimentar—el resto (instalación de librerías, datasets y scripts) lo instalamos juntos en el curso

You’ve just stumbled upon the most complete, in-depth Computer Vision course online.Whether you want to:- build the skills you need to get your first Computer Vision programming job- move to a more senior software developer position- become a computer scientist mastering in computation- or just learn Computer Vision to be able to work with your own projects quickly....this complete Computer Vision Masterclass is the course you need to do all of this, and more.This course is designed to give you the Computer Vision skills you need to become a Computer Vision expert. By the end of the course, you will understand Computer Vision extremely well and be able to work with your own Computer Vision projects and be productive as a computer scientist and software developer.What makes this course a bestseller?Like you, thousands of others were frustrated and fed up with fragmented Youtube tutorials or incomplete or outdated courses which assume you already know a bunch of stuff, as well as thick, college-like textbooks able to send even the most caffeine-fuelled coder to sleep.Like you, they were tired of low-quality lessons, poorly explained topics, and confusing info presented in the wrong way. That’s why so many find success in this complete Computer Vision course. It’s designed with simplicity and seamless progression in mind through its content.This course assumes no previous coding experience and takes you from absolute beginner core concepts. You will learn the core Computer Vision skills and master logic programming. It's a one-stop shop to learn Computer Vision. If you want to go beyond the core content you can do so at any time.Here’s just some of what you’ll learn(It’s okay if you don’t understand all this yet, you will in the course)Understand the formation mechanisms of Digital Images and the

Master Deep Learning and Computer Vision: From Foundations to Cutting-Edge Techniques Elevate your career with a comprehensive deep dive into the world of machine learning, with a focus on object detection, image classification, and object tracking.This course is designed to equip you with the practical skills and theoretical knowledge needed to excel in the field of computer vision and deep learning. You'll learn to leverage state-of-the-art techniques, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and advanced object detection models like YOL Ov8.Key Learning Outcomes:Fundamental Concepts:Grasp the core concepts of machine learning and deep learning, including supervised and unsupervised learning.Understand the mathematical foundations of neural networks, such as linear algebra, calculus, and probability theory.Computer Vision Techniques:Master image processing techniques, including filtering, noise reduction, and feature extraction.Learn to implement various object detection models, such as YOL Ov8, Faster R-CNNs, and SSD.Explore image classification techniques, including CNNs architectures like Res Net, Inception, and Efficient Net.Dive into object tracking algorithms, such as SORT, DeepSORT, and Kalman filtering.Practical Projects:Build real-world applications, such as license plate recognition, traffic sign detection, and sports analytics.Gain hands-on experience with popular deep learning frameworks like TensorFlow and PyTorch.Learn to fine-tune pre-trained models and train custom models for specific tasks.Why Choose This Course?Expert Instruction: Learn from experienced ins

Latest update: I will show you both how to use a pretrained model and how to train one yourself with a custom dataset on Google Colab.This course is a complete guide for setting up TensorFlow object detection api, Transfer learning and a lot moreI think what you’ll find is that, this course is so entirely different from the previous one, you will be impressed at just how much material we have to cover.Here is the details about the project.Here we will star from colab understating because that will help to use free GPU provided by google to train up our model.We’re going to bridge the gap between the basic CNNs architecture you already know and love, to modern, novel architectures such as Res Net, and Inception.We will understand object detection modules in detail using both TensorFlow object detection api as well as YOLO algorithms.We’ll be looking at a state-of-the-art algorithm called RESNET and Mobile NetV2 which is both faster and more accurate than its predecessors.One best thing is you will understand the core basics of CNNs and how it converts to object detection slowly.I hope you’re excited to learn about these advanced applications of CNNs Yolo and TensorFlow, I’ll see you in class!AMAGING FACTS:· This course give’s you full hand’s on experience of training models in colab GPU.· Instead of focusing on the detailed inner workings of CNNs (which we've already done), we'll focus on high-level building blocks. The result? Almost zero math.· Another result? No complicated low-level code such as that written in TensorFlow, Theano,YOLO, or PyTorch (although some optional exercises may contain them for the very advanced students). Most of the course will be in Keras which means a lot of the tedious, repetitive stuff is written for you.

Master Real-Time Object Detection with Deep Learning Dive into the world of computer vision and learn to build intelligent video analytics systems. This comprehensive course covers everything from foundational concepts to advanced techniques, including:Video Analytics Basics: Understand the 3-step process of capturing, processing, and saving video data.Object Detection Powerhouse: Explore state-of-the-art object detection models like Haar Cascade, HOG, Faster RCNN, R-FCN, SSD, and YOLO.Real-World Applications: Implement practical projects like people footfall tracking, automatic parking management, and real-time license plate recognition.Deep Learning Mastery: Learn to train and deploy deep learning models for image classification and object detection using frameworks like TensorFlow and Keras.Hands-On Experience: Benefit from line-by-line code walkthroughs and dedicated support to ensure a smooth learning journey.Exciting News!We've just added two new, hands-on projects to help you master real-world computer vision applications:Real-Time License Plate Recognition System Using YOL Ov3: Dive deep into real-time object detection and recognition.Training a YOL Ov3 Model for Real-Time License Plate Recognition: Learn to customize and train your own YOL Ov3 model. Don't miss this opportunity to level up your skills!Why Enroll?Industry-Relevant Skills: Gain in-demand skills to advance your career in AI and machine learning.Practical Projects: Build a strong portfolio with real-world applications.Expert Guidance: Learn from experienced instructors and get personalized support.

Computer Vision Web Development course will take you from the very basics right up till you are comfortable enough in creating your own web apps. By the end of the course, you will have the skills and knowledge to develop your own computer vision applications on the web. Whether it’s Custom Object Detection or simple Color Detection you can do almost everything on the web.This comprehensive course covers a range of topics, including:Basics of Web Development Basics of Computer Vision Basics of OpenCV js Computer Vision and Web Integration Graphical Interface Video Processing in the Browser using OpenCV.js Object Detection Custom Object Detection TensorFlow for Java Script Deep Learning on the Web Computer Vision Advanced Creating 10+ CV Web Apps Building a Photoshop Web Application with OpenCV.js Real-Time Face Detection in the Browser with OpenCV.js & Haar Cascade Classifier Real-time Object Detection in the Browser using YOL Ov8 and TensorFlow.js Object Detection in Images & Videos in the Browser using YOL Ov8 & TensorFlow.js Personal Protective Equipment (PPE) Detection in the Browser using YOL Ov8 and TensorFlow.js American Sign Language (ASL) Letters Detection in the Browser using YOL Ov8 and TensorFlow.js Licence Plate Detection and Recognition in the Browser using YOL Ov8 and Tesseract.js