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cv-tricks.com: Learn computer vision and artificial intelligence

Repository for all the tutorials and codes shared at cv-tricks.com

Tensorflow tutorials:

#1 10 minutes Practical TensorFlow lesson for quick learners: If you have just heard about Tensorflow and are looking to get started, then go to this blog post http://cv-tricks.com/artificial-intelligence/deep-learning/deep-learning-frameworks/tensorflow-tutorial/ and in the end we train a simple linear classifier to absorb what we have studied. Code is here https://github.com/sankit1/cv-tricks.com/tree/master/Tensorflow-tutorials/first_tutorial

#2 Build image classifier using Tensorflow: In this blogpost http://cv-tricks.com/tensorflow-tutorial/training-convolutional-neural-network-for-image-classification/ , We build a simple convolutional neural network using Tensorflow. Code is here: https://github.com/sankit1/cv-tricks.com/tree/master/Tensorflow-tutorials/tutorial-2-image-classifier.

#3 Learn to save and restore Tensorflow Models: BlogPost here: http://cv-tricks.com/tensorflow-tutorial/save-restore-tensorflow-models-quick-complete-tutorial/

#4 Tutorial to Learn TF-slim and run VGG, Inception and other popular networks. Code here: https://github.com/sankit1/cv-tricks.com/tree/master/Tensorflow-tutorials/Tensorflow-slim-run-prediction

#5. Installing and getting started with Keras. Code here: https://github.com/sankit1/cv-tricks.com/tree/master/Tensorflow-tutorials/Keras-Tensorflow-tutorial

Advanced Topics(Blogs):

  1. Object Detection algorithms. http://cv-tricks.com/artificial-intelligence/object-detection-using-deep-learning-for-advanced-users-part-1/
  2. Image Segmentation using Tensorflow . http://cv-tricks.com/image-segmentation/transpose-convolution-in-tensorflow/
  3. Show-Attend-and-Tell: Finer details of Image Captioning. http://cv-tricks.com/image-segmentation/transpose-convolution-in-tensorflow/
  4. Accelerating CNNs on Raspberry Pi: http://cv-tricks.com/artificial-intelligence/deep-learning/accelerating-convolutional-neural-networks-on-raspberry-pi/

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