Build Image Recognition Model In Python in 20 min

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Dive into the world of Deep Learning and master image recognition using Convolutional Neural Networks (CNNs) in Python! This comprehensive tutorial takes you from the basics to building and testing your own powerful image recognition model. No prior deep learning experience required!

This tutorial covers:

The fundamentals of Deep Learning
Setting up your Python environment for CNN development
Data preparation and augmentation techniques
Building and training a CNN model
Evaluating model performance
Making predictions with your trained model
Saving your model for future use

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Timestamps:
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00:00 Intro
00:30 What is Deep Learning
02:19 Install libraries
02:48 Import libraries
04:19 Read the files
05:58 Define parameters
07:36 Data augmentation
08:27 Split the data into training, testing, validation
09:28 Print any of the images
10:02 Load the model ResNet50
11:18 Freeze convolutional base
11:45 Build model
13:15 Compile model
14:51 Fitting the model
17:51 End of model training
18:08 Model evaluation
19:12 Function to make predictions
20:35 Making Predictions
21:05 Saving the model
21:17 Next steps with the model

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About me
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Hi, my name is Karina and I'm a finance person turned data person.

My mission is to transform intimidating tech into accessible tools. I aim to empower 1 million people to harness the power of AI, Python, SQL, and Excel to work smarter, not harder.

Contact
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Youtube: youtube comments are by far the best way to get a response from me!

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Social Media:
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#pythonprogramming #imagerecognition #ml