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via Udemy |
Go to Course: https://www.udemy.com/course/introduction-au-deep-learningtensorflow-et-keras/
Certainly! Here's a comprehensive review and recommendation for the Coursera course based on your description: --- **Course Review and Recommendation: Computer Vision and Image Classification Basics** If you're interested in diving into computer vision and understanding how image classification works, this Coursera course offers a solid foundation. Designed for beginners and those looking to expand their knowledge in deep learning applications, the course emphasizes practical skills through hands-on projects. **What You'll Learn:** The course introduces the fundamental concepts of image classification, particularly how to categorize images into different classes. An initial project involves binary classification, where you will learn how to distinguish between two categories—setting a strong groundwork for more complex tasks. **Course Content & Projects:** 1. **Binary Image Classification:** Practice classifying images into two categories using a straightforward project. 2. **Deepening Your Knowledge:** The course also includes a more comprehensive follow-up module that covers multi-class image classification, using the Fashion-MNIST dataset to categorize clothing items into ten different classes with an impressive accuracy of 96% using TensorFlow and Keras. You will understand how convolutional neural networks (CNNs) work in recognizing complex patterns. 3. **Building from Scratch:** The course stands out by guiding you through coding a perceptron from scratch without relying on high-level libraries, providing a deeper understanding of the mechanics behind neural networks. 4. **Advanced Techniques:** You will explore techniques like image augmentation and transfer learning, essential for improving model performance and tackling real-world datasets such as dogs vs. cats, with 3,000 images. **Who Should Take This Course?** This course is ideal for beginners and intermediate learners who want to get practical experience and a solid theoretical understanding. It's especially useful if you're interested in developing skills that can be applied to facial recognition, emotion detection, and other computer vision tasks. **Why Recommend This Course?** - Hands-on projects that reinforce learning - Clear progression from basic to more advanced topics - Real-world datasets and challenges to prepare you for practical applications - Opportunity to learn both coding from scratch and leveraging powerful libraries like TensorFlow and Keras **Final Thoughts:** This course provides an excellent starting point for anyone eager to learn about image classification and computer vision. Coupled with the more comprehensive follow-up course on deep learning with TensorFlow and Keras, you will be well-equipped to tackle a variety of image-based machine learning projects. --- Feel free to explore the more advanced course by visiting the instructor's profile for a broader learning experience. Happy learning!
Cette formation vous permettra de comprendre la vision par ordinateur en classifiant des images.Vous comprendrez c'est quoi la classification d'images en réalisant un projet de classification d'images binaire. Après cette formation vous pouvez prendre ma formation Deeplearning: classification d'images avec tensorflow,Keras que vous trouverez en cliquant sur mon profile qui elle est plus complète car dans celle là nous réaliserons 3 différents projets:1 - coder un perceptron de zéro: qui vous permettra de comprendre comment un modèle de deep learning marche, car nous allons coder un perceptron (réseau de neurone à une seule couche) sans utiliser tensorflow 2 - classification d'images multi classes: nous allons classifier des images d'articles de modes(sac, sandale, sneaker, tee-shirt etc..) en 10 classes différentes avec la base de donnée fashion-mnist et cette fois si avec tensorflow et keras et les réseaux de neurones convolutifs(nous obtiendrons une précision de 96%)3 - classification d'images binaire: nous allons classifier des images de chats et de chien avec une base de données de 3000 photos de chien et de chat. dans ce dernier projet nous allons apprendre plusieurs techniques comme l'augmentation d'image, et l'apprentissage par transfert.Avec les connaissances acquises dans ce cours vous allez pouvoir classifier n'importe qu'elle catégorie d'image et vous allez pouvoir vous lancez dans d'autres applications de la vision par ordinateur tels que la reconnaissance faciale, la détection d'émotion etc...