Uploaded April 2022 | Updated September 2026, 2 hours ago

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Get the Code github.com/nicknochnack/ImageClassification

So...you wanna build your own image classifier eh? Well in this tutorial you're going to learn how to do exactly that...FROM SCRATCH using Python, Tensorflow and Keras. But best yet, you can do it on virtually any dataset. Go on, give it a go!

Links
Sigmoid Activation: en.wikipedia.org/wiki/Sigmoid_function
Relu Activation: en.wikipedia.org/wiki/Rectifier_(neural_networks)
Image Downloader Extension: chrome.google.com/webstore/detail/download-all-images/ifipmflagepipjokmbdecpmjbibjnakm?hl=en
Conv2D Layer: tensorflow.org/api_docs/python/tf/keras/layers/Conv2D
MaxPooling Layer: keras.io/api/layers/pooling_layers/max_pooling2d

Chapters
0:00 - Start
0:28 - Explainer
1:19 - PART 1: Building a Data Pipeline
3:08 - Installing Dependencies
8:30 - Getting Data from Google Images
23:12 - Load Data using Keras Utils
33:22 - PART 2: Preprocessing Data
35:56 - Scaling Images
42:23 - Partitioning the Dataset
47:34 - PART 3: Building the Deep Neural Network
48:21 - Build the Network
1:02:32 - Training the DNN
1:06:37 - Plotting Model Performance
1:09:50 - PART 4: Evaluating Perofmrnace
1:10:38 - Evaluating on the Test Partition
1:13:59 - Testing on New Data
1:20:39 - PART 5: Saving the Model
1:21:08 - Saving the model as h5 file
1:24:43 - Wrap Up

Oh, and don't forget to connect with me!
LinkedIn: bit.ly/324Epgo
Facebook: bit.ly/3mB1sZD
GitHub: bit.ly/3mDJllD
Patreon: bit.ly/2OCn3UW
Join the Discussion on Discord: bit.ly/3dQiZsV

Happy coding!
Nick

P.s. Let me know how you go and drop a comment if you need a hand!
#deeplearning #python