Book Image

The Deep Learning with Keras Workshop

By : Matthew Moocarme, Mahla Abdolahnejad, Ritesh Bhagwat
1 (1)
Book Image

The Deep Learning with Keras Workshop

1 (1)
By: Matthew Moocarme, Mahla Abdolahnejad, Ritesh Bhagwat

Overview of this book

New experiences can be intimidating, but not this one! This beginner’s guide to deep learning is here to help you explore deep learning from scratch with Keras, and be on your way to training your first ever neural networks. What sets Keras apart from other deep learning frameworks is its simplicity. With over two hundred thousand users, Keras has a stronger adoption in industry and the research community than any other deep learning framework. The Deep Learning with Keras Workshop starts by introducing you to the fundamental concepts of machine learning using the scikit-learn package. After learning how to perform the linear transformations that are necessary for building neural networks, you'll build your first neural network with the Keras library. As you advance, you'll learn how to build multi-layer neural networks and recognize when your model is underfitting or overfitting to the training data. With the help of practical exercises, you’ll learn to use cross-validation techniques to evaluate your models and then choose the optimal hyperparameters to fine-tune their performance. Finally, you’ll explore recurrent neural networks and learn how to train them to predict values in sequential data. By the end of this book, you'll have developed the skills you need to confidently train your own neural network models.
Table of Contents (11 chapters)
Preface

Recurrent Neural Networks (RNNs)

RNNs are a class of neural networks that are built on the concept of sequential memory. Unlike traditional neural networks, an RNN predicts the results in sequential data. Currently, an RNN is the most robust technique that's available for processing sequential data.

If you have access to a smartphone that has Google Assistant, try opening it and asking the question: "When was the United Nations formed?" The answer is displayed in the following screenshot:

Figure 9.2: Google Assistant's output

Now, ask a second question, "Why was it formed?", as follows:

Figure 9.3: Google Assistant's contextual output

Now, ask the third question, "Where are its headquarters?", and you should get the following answer:

Figure 9.4: Google Assistant's output

One interesting thing to note here is that we only mentioned the "United Nations...