Deep Learning – Image Classification Tutorial step by step (for Beginners) (python / TensorFlow)
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This video contains a basic level tutorial for implementing image classification using deep learning library such as Tensorflow.
1. Overview of concepts (Brainstorming) Image Classification
2. Image loading (four different methods)
(i) Python Imaging Library
(ii) Open CV
(iii) IPython.display
(iv) Tensorflow.Keras API – Preprocessing
3. Deep learning architectures
(i) Model Loading (MobileNet etc)
(ii) Predictions
4. Decoding the predictions into labels
Source
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Thank you for this amazing video, sir! I'm now more understand about the Tensorflow and image classification. May I know, can I use Microsoft Visual Studio instead of Anaconda? Are they have the same function? And lastly, I want to know, this method can be use in Raspberry Pi for image processing sir with camera implement with it? Thank you 😄
Thank you so much for fundamental! How can I train my own images? and do the classification. Do you have any video for that?
Hello sir , i can't import imagenet_utils could you please help me to solve this issue.
(it shown me this bro "ImportError: cannot import name 'imgenet_utils' from 'tensorflow.keras.applications' (unknown location)
")
Brother are you from Bangladesh?
Can u make more videos on this possibly on food recognition using a large dataset? PLS ty
Shan bhai! If I want to multiply a number with a specific row in 3×3 matrix in numpy array, then how should I do that?
Great. Please do work on the tutorial for Python too!
Amazing… Finally, someone teaching very good
good job.
Well done Shan