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\nHow to Make an AI Read Your Handwriting (LAB)\n

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\n\nPublisher:\n\nCrash Course\n\n\n
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\nJohn Green Bot wrote his first novel! Today, in our first ever Lab we’re going to program a neural network to recognize handwritten letters to convert the first part of John Green Bot’s novel into typed text. To do this we’re going to...\nJohn Green Bot wrote his first novel! Today, in our first ever Lab we’re going to program a neural network to recognize handwritten letters to convert the first part of John Green Bot’s novel into typed text. To do this we’re going to import a labeled dataset, called EMNIST, we’ll to use a pre-written library called SKLearn to build the network, we’ll train and tweak our code until it’s accurate (enough), and then we’ll use our newly trained network to convert John Green Bot’s handwritten pages. We created this project in a way that you don’t have to install anything on your computer, the only thing you’ll need to get started is a Google account and a sense of adventure! To run the Colaboratory file (link at the top) you’ll have to click “open in playground” at the top of the page OR open the File Menu and click “Save a Copy to Drive.” From there you can change, tweak, and edit the code as you wish. We also left text around and within the code to help you along the way.\n
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Resource Details

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Educator Rating
Not yet Rated
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Media Length
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16:56
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Grade
12th - Higher Ed
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Subjects
STEM
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Media Type
Instructional Videos
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Source:
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\nCrash Course Artificial Intelligence\n\n
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Date
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2019
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Language
English
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Audiences
For Teacher Use
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Usage Permissions
Fine Print: Educational Use
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Concepts

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work, handwriting, data, accuracy, numbers, john green, artificial intelligence, computer science
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Additional Tags

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training set, robot, 000 images, neural network, training, type text, image, images, label, labeled images, handwritten letters, 50 neurons, sklearn, label data, network, labeled, machine learning, networks, ai, data set, correct, hidden layers, letter, segmentation problem, testing set, emnist, correct values, learn, program, crash course
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Classroom Considerations

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Best For: Explaining a topic
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