YPDL-Build-a-movie-recommendation-engine-with-TensorFlow
Playing-Cards-Classification-TensorFlow-CNN
YPDL-Build-a-movie-recommendation-engine-with-TensorFlow | Playing-Cards-Classification-TensorFlow-CNN | |
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1 | 1 | |
8 | 0 | |
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0.0 | 10.0 | |
almost 2 years ago | over 1 year ago | |
Jupyter Notebook | Jupyter Notebook | |
Apache License 2.0 | - |
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YPDL-Build-a-movie-recommendation-engine-with-TensorFlow
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Your Path to Deep Learning
Workshop 4 Resources
Playing-Cards-Classification-TensorFlow-CNN
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42069 😳
yeah, i was uploading my TensorFlow Lite model lol https://github.com/0xN1nja/Playing-Cards-Classification-TensorFlow-CNN
What are some alternatives?
Practical_RL - A course in reinforcement learning in the wild
One-Piece-Image-Classifier - A quick image classifier trained with manually selected One Piece images.
labml - 🔎 Monitor deep learning model training and hardware usage from your mobile phone 📱
Food-Recipe-CNN - food image to recipe with deep convolutional neural networks.
garrascobike-core - Core of the Garrascobike project
tutorial-face-mask-detection - In this project, we develop a pipeline to detect unmasked faces in images. This can, for example, be used to alert people that do not wear a mask when entering a building.
YPDL-Identify-Handwritten-Digits-using-CNN-with-TensorFlow - Identify Handwritten Digits using CNN with TensorFlow
face-mask-detection - In this project, we develop a pipeline to detect unmasked faces in images. This can, for example, be used to alert people that do not wear a mask when entering a building. [Moved to: https://github.com/datarootsio/tutorial-face-mask-detection]
YPDL-Recurrent-Neural-Networks-using-TensorFlow-Keras - Build a recurrent neural network using TensorFlow and Keras.
blog-tpi-jupyter - Terraform Provider Iterative + Jupyter + TensorBoard + AWS/Azure/GCP/K8s
YourPathToDeepLearning - Sequel to our infamous Your Path to AI Series. We are introducing this new advanced level series for audience interested to specialise in Deep Learning. This repository holds all the resources for the series for you to catch up in case you have missed it.