In this post, let us see how to build a deep learning model using Keras. If you haven't installed Tensorflow and Keras, I will show the simple way to install these two modules.

### 1. Installing Tensorflow and Keras

- Open Anaconda Navigator. Under Environments, create new environment in Python 3.6.

Create a new environment in Anaconda- Python 3.6 |

Created a new environment |

- Open terminal and pip install Tensorflow and Keras

Open Terminal |

Use the appropriate option for your computer (From Tensorflow website) |

- pip install tensorflow

install Tensorflow |

- then, pip install keras

install Keras |

- Now install Jupyter Notebook on this environment and launch

- import tensorflow and keras

Mission successful! |

### 2. Building Model using Keras

#### 2.1 Four steps

Keras is simple to use. There are four steps in building a neural network model in Keras.

- Define the architecture
- Compile
- Fit
- Predict

In the following picture, I have shown these four steps (basic code is taken from here).

As you can see, first we have imported libraries.

####
**
a) Define the architecture**

####
**b) Compile**

- Loss function,
- Optimizer and
- Metrics

**b1) Loss function**

In case of Loss function, commonly used are the

- mean_squared_error: commonly used for regression tasks
- mean_absolute_percentage_error
- categorical_crossentropy (Used for classification problems where y is one-hot-encoded, if not we can use to_categorical option to one-hot-encode y)

For more loss functions, refer this page.

**b2) Optimizer**

Commonly used optimizers are

- 'sgd' (Stochastic gradient descent)
- 'adam' (adam stands for adaptive moment estimation)

We can tune the learning rates, decay, momentum etc for better performance.

**b3) Metrics**

And in case metrics to measure the performance of the model, commonly used is the 'accuracy'

####
**c) Fit**

model.fit(X, target, validation_split=0.3, epochs=30, callbacks=[early_stopping_monitor])

####
**d) Predict**

### Summary

In this post, we have seen

- how to install Tensorflow and Keras
- Four steps of basic model building in Keras
- Some important concepts/hyperparameters in those four steps

###
**3. References**

- https://keras.io/ has all the resources to learn Keras.
- For installing Tensorflow and Keras, refer https://towardsdatascience.com/python-environment-setup-for-deep-learning-on-windows-10-c373786e36d1
- Also you may refer this page for installing Keras
- Excellent blogpost series on training neural networks https://towardsdatascience.com/how-do-we-train-neural-networks-edd985562b73