In this episode we're going to train our own image classifier to detect Darth Vader images.
The code for this repository is here:
https://github.com/llSourcell/tensorflow_image_classifier
I created a Slack channel for us, sign up here:
https://wizards.herokuapp.com/
The Challenge:
The challenge for this episode is to create your own Image Classifier that would be a useful tool for scientists. Just post a clone of this repo that includes your retrained Inception Model (label it output_graph.pb). If it's too big for GitHub, just upload it to DropBox and post the link in your GitHub README. I'm going to judge all of them and the winner gets a shoutout from me in a future video, as well as a signed copy of my book 'Decentralized Applications'.
This CodeLab by Google is super useful in learning this stuff:
https://codelabs.developers.google.com/codelabs/tensorflow-for-poets/?utm_campaign=chrome_series_machinelearning_063016&utm_source=gdev&utm_medium=yt-desc#0
This Tutorial by Google is also very useful:
https://www.tensorflow.org/versions/r0.9/how_tos/image_retraining/index.html
This is a good informational video:
https://www.youtube.com/watch?v=VpDonQAKtE4
Really deep dive video on CNNs:
https://www.youtube.com/watch?v=FmpDIaiMIeA
I love you guys! Thanks for watching my videos and if you've found any of them useful I'd love your support on Patreon:
https://www.patreon.com/user?u=3191693
Much more to come so please SUBSCRIBE, LIKE, and COMMENT! :)
edit: Credit to Clarifai for the first conv net diagram in the video
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