Get the Code [ Ссылка ]
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: [ Ссылка ]
Relu Activation: [ Ссылка ]
Image Downloader Extension: [ Ссылка ]
Conv2D Layer: [ Ссылка ]
MaxPooling Layer: [ Ссылка ]
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: [ Ссылка ]
Facebook: [ Ссылка ]
GitHub: [ Ссылка ]
Patreon: [ Ссылка ]
Join the Discussion on Discord: [ Ссылка ]
Happy coding!
Nick
P.s. Let me know how you go and drop a comment if you need a hand!
#deeplearning #python
