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Google Cloud via Coursera |
Go to Course: https://www.coursera.org/learn/image-understanding-tensorflow-gcp
### Course Review: Computer Vision Fundamentals with Google Cloud In today’s data-driven world, the ability to extract meaningful information from images using computer vision is a critical skill across various industries, from healthcare to self-driving cars. For those eager to dive into this promising field, the **Computer Vision Fundamentals with Google Cloud** course on Coursera stands out as an excellent starting point. #### Course Overview This comprehensive course provides an insightful introduction to the vast realm of computer vision. It covers a wide array of use cases and methodologies for utilizing machine learning (ML) to solve specific visual recognition problems. Learners will explore different strategies, ranging from leveraging pre-built machine learning models to developing custom solutions with advanced techniques such as deep neural networks (DNN) and convolutional neural networks (CNN). The course also emphasizes crucial concepts like data augmentation and feature extraction to enhance model accuracy. #### Syllabus Breakdown The course is well-structured, guiding participants through fundamental and advanced topics in a logical progression. Below is an overview of the syllabus: - **Introduction** - The course begins with a welcome and an overview of what to expect, setting a clear agenda for learners. - **Introduction to Computer Vision and Pre-built ML Models for Image Classification** - This module lays the foundation by defining computer vision and explaining how pre-built models can be utilized for effective image classification. - **Vertex AI and AutoML Vision on Vertex AI** - Dive into Google Cloud’s Vertex AI platform, where you will learn about leveraging AutoML Vision to simplify the process of training and deploying machine learning models. - **Custom Training with Linear, Neural Network and Deep Neural Network Models** - This section is crucial as it walks learners through the custom training of different models, enabling the creation of tailored solutions to specific challenges. - **Convolutional Neural Networks** - Focused on one of the most powerful architectures in computer vision, this module covers CNNs and their application in processing and analyzing visual data. - **Dealing with Image Data** - Gain practical knowledge about managing image datasets, which is essential for building robust models. - **Summary** - The course concludes with a recap of the key takeaways, ensuring that learners leave with a solid understanding of the material covered. #### Learning Experience The course is designed with both beginners and more experienced practitioners in mind. It features a mix of theoretical discussions and practical hands-on labs, allowing students to apply their knowledge directly. One of the most appealing aspects is the integration with Google Cloud tools, which familiarizes learners with industry-leading platforms and practices. The use of interactive quizzes and practical projects not only reinforces learning but also gives students tangible experience that enhances their portfolios. Furthermore, by the end of the course, participants will have a solid grasp of how to tackle real-world computer vision scenarios. #### Recommendation I highly recommend **Computer Vision Fundamentals with Google Cloud** for anyone interested in the intersection of technology and visual data. Whether you are looking to kickstart a career in data science, enhance your skill set, or simply explore the exciting world of machine learning, this course offers a balanced mix of theory and practical application. In conclusion, the blending of foundational knowledge with advanced techniques, coupled with the reputable backing of Google Cloud, makes this course a valuable investment in your educational journey. Sign up today to unlock the potential of computer vision and transform the way you work with images!
Introduction
Course Introduction
Introduction to Computer Vision and Pre-built ML Models for Image ClassificationIntroduction to Computer Vision and Pre-built ML Models for Image Classification
Vertex AI and AutoML Vision on Vertex AILearn about Vertex AI and AutoML Vision on Vertex AI
Custom Training with Linear, Neural Network and Deep Neural Network modelsLearn about Custom Training with Linear, Neural Network and Deep Neural Network models
Convolutional Neural NetworksLearn about Convolutional Neural Networks
Dealing with Image DataLearn about dealing with Image Data
SummaryCourse Summary
This course describes different types of computer vision use cases and then highlights different machine learning strategies for solving these use cases. The strategies vary from experimenting with pre-built ML models through pre-built ML APIs and AutoML Vision to building custom image classifiers using linear models, deep neural network (DNN) models or convolutional neural network (CNN) models. The course shows how to improve a model's accuracy with augmentation, feature extraction, and fine-
Great course, great team, First week is as it was expected but second is week is outstanding. The Neural Architecture search(NAS) is outstanding. Super job.
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Some of the content could not be completed/needs to be updated. I ran into a few bugs/errors, but still wanted to learn the content/gain the certificate.
I would like to work with TPUs in one laboratory. Also, I would like to see how the pattern of image was formed throught the convolutional neural network in a lab.
a real eye opener education, it gave me lots of answers to the questions i had in this area. it is just amazing that ML can differ between roses and tulips !