Unleash the Power of AI with Custom Vision

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Unleash the Power of AI with Custom Vision

Table of Contents

  1. Introduction to Artificial Intelligence
  2. Definition of Artificial Intelligence
  3. Definition of Machine Learning
  4. Definition of Custom Vision
  5. Introduction to Microsoft Azure
  6. Overview of Custom Vision
  7. Creating a Custom Vision Instance on Microsoft Azure
  8. Uploading and Labeling Images for Training
  9. Training the Custom Vision Model
  10. Making Predictions with the Custom Vision Model
  11. Other Applications of Custom Vision
  12. Certification and Resources for AI Learning
  13. Conclusion and Thank You

Introduction to Artificial Intelligence with Custom Vision

Artificial Intelligence (AI) is a field of computer science that focuses on creating machines or systems that can make intuitive decisions Based on training they undergo. AI allows computers to mimic human behavior by making informed decisions and inferences from data. Machine Learning is a subset of AI that teaches systems to identify Patterns in data, enabling them to make inferences and decisions based on past experiences. Custom Vision is a subdomain of AI that deals with visual processing, specifically identifying and categorizing images. This article will provide an overview of Custom Vision and guide you through the process of training and using a Custom Vision model on Microsoft Azure.

Definition of Artificial Intelligence

Artificial Intelligence refers to computers or machines performing tasks that are typically associated with human intelligence. Unlike traditional programming, where computers follow predefined step-by-step procedures to produce outputs, AI enables computers to make uninformed decisions by analyzing and interpreting data. AI aims to Create machines or systems that can mimic human behavior and make intuitive decisions.

Definition of Machine Learning

Machine Learning is a subset of Artificial Intelligence that focuses on teaching systems to identify patterns in data and make inferences based on past experiences. It involves training a model using a set of labeled data and using this model to predict or classify new, unlabeled data. Machine Learning models can learn and improve over time as more data becomes available, allowing them to make more accurate predictions or classifications.

Definition of Custom Vision

Custom Vision is a sub-domain of Artificial Intelligence that specifically deals with visual processing and image recognition. It is a cognitive service offered by Microsoft Azure, a cloud computing service provided by Microsoft. Custom Vision allows users to build, deploy, and improve their own image classification models. It enables computers to "see" and make predictions or classifications based on the images it is trained on.

Introduction to Microsoft Azure

Microsoft Azure is a cloud computing service offered by Microsoft that provides a range of computing services over the internet. It allows users to build, deploy, and manage applications and services through Microsoft-managed data centers. Azure provides various services and resources for different domains, including Artificial Intelligence, Machine Learning, and Custom Vision.

Overview of Custom Vision

Custom Vision is a web-based application developed by Microsoft that allows users to identify, classify, and categorize images based on their content. It offers pre-built training models that eliminate the need for coding and technical expertise. The process of using Custom Vision involves three main steps: uploading and labeling images for training, training the model, and making predictions based on the trained model.

Creating a Custom Vision Instance on Microsoft Azure

To begin using Custom Vision, you need to create an instance or resource on Microsoft Azure. This instance provides the necessary infrastructure and resources for training and deploying your Custom Vision model. By creating a resource on Azure, you gain access to a range of computing services and tools that support your machine learning endeavors. You can choose the region for your instance based on geographical proximity to improve performance and efficiency.

Uploading and Labeling Images for Training

Once you have created a Custom Vision instance, you can start uploading and labeling images for training. Custom Vision requires a set of labeled images to train the model. Each image is assigned a tag based on its content or category. For example, if you want to classify different breeds of dogs, you would upload images of each breed and assign appropriate tags. It is recommended to upload a sufficient number of images for each tag to improve the accuracy of the trained model.

Training the Custom Vision Model

After the images have been uploaded and labeled, you can proceed to train the Custom Vision model. Training involves using the uploaded images to teach the model to recognize and classify objects or patterns. The training process analyzes the images, identifies patterns, and creates a model that can make predictions or classifications based on the learned data. It is important to note that machine learning models are not always 100% accurate and may have some margin of error.

Making Predictions with the Custom Vision Model

Once the Custom Vision model has been trained, you can use it to make predictions or classifications on new, unseen images. The model takes an input image and analyzes its content to determine which category or tag it belongs to. The model assigns a probability score to each category, indicating how confident it is in its prediction. Higher probability scores suggest a higher likelihood of accuracy. Making predictions with the Custom Vision model allows for automated image recognition and classification tasks.

Other Applications of Custom Vision

Custom Vision has various applications beyond image classification. It can be used for object detection, semantic segmentation, face detection, analysis and recognition, and optical character recognition. These functionalities allow computers to analyze and understand different elements within images, enabling applications such as surveillance systems, autonomous vehicles, and document processing.

Certification and Resources for AI Learning

To enhance your knowledge and expertise in Artificial Intelligence, Microsoft offers certifications and resources for AI learning. Microsoft Learn is a platform specifically designed for interactive learning of different Microsoft technologies. It provides learning paths, modules, and resources for students to develop skills in AI, Machine Learning, and other domains. Microsoft also offers free certifications for fundamental-level certificates, allowing students to enhance their credentials and knowledge in specific Microsoft technologies.

Conclusion and Thank You

In conclusion, Custom Vision is a powerful tool in the field of Artificial Intelligence that enables image recognition and classification. With Microsoft Azure's Custom Vision service, users can easily build, deploy, and improve their own image identifier models. By utilizing the training and prediction capabilities of Custom Vision, computers can make informed decisions based on visual content just as humans do. Thank you for joining this workshop, and I hope it has provided valuable insights into the world of AI and Custom Vision.

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