Image Classification

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• The MNIST Database | Y. LeCun, C. Cortes, and C. Burges

Classify Images Using Python & Machine Learning Classify Images Using Machine Learning & Convolutional Neural Networks (CNN)

Using Machine Learning to Classify Multispectral Imagery Watch this informational webinar and learn about how MicaSense and Picterra can help you solve complex image classification problems. MicaSense’s precise and accurate multispectral sensors help capture radiometrically accurate drone-based imagery, while Picterra’s “image analysis made easy” approach offers users a straightforward solution for creating and training machine-learning algorithms; no background in data science or coding required!

Lecture 2: Image Classification Lecture 2 introduces image classification as a core computer vision problem. We see that the image classification task is made challenging by the semantic gap, but that solutions to this task can be used as a building block in other more complicated computer vision systems. We introduce machine learning as a data-driven approach to solving hard problems like image classification. We discuss several common classification datasets in computer vision. Finally we introduce K-Nearest Neighbors (KNN) as our first machine learning algorithm. This leads to a discussion of hyperparameters and cross-validation strategies that will be crucial for all the machine learning algorithms we will later use. Slides: https://myumi.ch/ovgw7

Image Classification using PyTorch in 2020 A virtual hands-on interactive PyTorch workshop, organized by People In Data together with Facebook DevC Stockholm. You will be guided through the code and implement your own CNN model! The only thing you need to bring is your Google account (as we will be using Google Colab) and your curiosity. This webinar will be led by Pranjal Chaubey who is an AI mentor at Udacity and has done workshops for Developer Circles Hyderabad. He is a keen learner of anything data and always eager to share his knowledge.

Deep Learning for Fruit Classification | CNN | Flask | Project | Code Warriors Hello Everyone, Code Warriors brings the opportunity to build Deep learning-based Fruit Classification. It's going to be amazing and full of knowledge because mentors are going to teach you it from scratch and the session is completely project-based. The specialty of this event is that while learning to make a model for the classification of fruits, you will also be able to know whether the fruits are fresh or rotten. The ability for a computer to be able to analyze an image and tell you what’s in it (image classification), whether it’s a banana, apple, or orange. Moreover, it will also predict that the fruit is fresh or rotten. This is a hands-on workshop. Certification of Completion will be provided. Pie & AI is a series of deeplearning.ai meetups. This time Code Warriors is going to host this event for you. That you all will learn some new skills. After the event is over, we will provide a survey link by filling in this survey, you are going to get a 50% discount promo code for your first-month membership for any deeplearning.ai course at Coursera.

How to Make an Image Classifier - Intro to Deep Learning #6 Siraj Raval We're going to make our own Image Classifier for cats & dogs in 40 lines of Python! First we'll go over the history of image classification, then we'll dive into the concepts behind convolutional networks and why they are so amazing.

Microsoft Lobe

• Lobe aims to make it easy for anyone to train machine learning models. Free, private desktop application that has everything you need to take your machine learning ideas from prototype to production. This version of Lobe learns to look at images using image classification - categorizing an image into a single label overall. We are working to expand to more types of problems and data in future versions.

Microsoft acquires Lobe, a drag and drop AI tool Daily Tech News Sept 13, 2018

Introducing Lobe | Build your first machine learning model in ten minutes. Lobe has everything you need to train machine learning in a free, easy to use app. Just show it examples of what you want it to learn, and it automatically trains a custom machine learning model that can be shipped in your app. Start training your machine learning model today with Lobe.