- Deep Learning with Keras Tutorial
- Deep Learning with Keras - Home
- Deep Learning with Keras - Introduction
- Deep Learning
- Setting up Project
- Importing Libraries
- Creating Deep Learning Model
- Compiling the Model
- Preparing Data
- Training the Model
- Evaluating Model Performance
- Predicting on Test Data
- Saving Model
- Loading Model for Predictions
- Conclusion
- Deep Learning with Keras Resources
- Deep Learning with Keras - Quick Guide
- Deep Learning with Keras - Useful Resources
- Deep Learning with Keras - Discussion
Deep Learning with Keras - Setting up Project
With this background, let us now start creating the project.
Setting Up Project
We will use Jupyter through Anaconda navigator for our project. As our project uses TensorFlow and Keras, you will need to install those in Anaconda setup. To install Tensorflow, run the following command in your console window:
>conda install -c anaconda tensorflow
To install Keras, use the following command −
>conda install -c anaconda keras
You are now ready to start Jupyter.
Starting Jupyter
When you start the Anaconda navigator, you would see the following opening screen.
Click ‘Jupyter’ to start it. The screen will show up the existing projects, if any, on your drive.
Starting a New Project
Start a new Python 3 project in Anaconda by selecting the following menu option −
File | New Notebook | Python 3
The screenshot of the menu selection is shown for your quick reference −
A new blank project will show up on your screen as shown below −
Change the project name to DeepLearningDigitRecognition by clicking and editing on the default name “UntitledXX”.