Book Image

The Deep Learning Workshop

By : Mirza Rahim Baig, Thomas V. Joseph, Nipun Sadvilkar, Mohan Kumar Silaparasetty, Anthony So
Book Image

The Deep Learning Workshop

By: Mirza Rahim Baig, Thomas V. Joseph, Nipun Sadvilkar, Mohan Kumar Silaparasetty, Anthony So

Overview of this book

Are you fascinated by how deep learning powers intelligent applications such as self-driving cars, virtual assistants, facial recognition devices, and chatbots to process data and solve complex problems? Whether you are familiar with machine learning or are new to this domain, The Deep Learning Workshop will make it easy for you to understand deep learning with the help of interesting examples and exercises throughout. The book starts by highlighting the relationship between deep learning, machine learning, and artificial intelligence and helps you get comfortable with the TensorFlow 2.0 programming structure using hands-on exercises. You’ll understand neural networks, the structure of a perceptron, and how to use TensorFlow to create and train models. The book will then let you explore the fundamentals of computer vision by performing image recognition exercises with convolutional neural networks (CNNs) using Keras. As you advance, you’ll be able to make your model more powerful by implementing text embedding and sequencing the data using popular deep learning solutions. Finally, you’ll get to grips with bidirectional recurrent neural networks (RNNs) and build generative adversarial networks (GANs) for image synthesis. By the end of this deep learning book, you’ll have learned the skills essential for building deep learning models with TensorFlow and Keras.
Table of Contents (9 chapters)
Preface

Long-Range Dependence/Influence

The sample mobile phone review we saw in the previous section was an example of a long-range dependence/influence – where a term/value in a sequence has an influence on the assessment of a lot of the subsequent terms/values. Consider the following example, where you need to fill in the blank with a missing country name: "After a top German university granted her admission for her Masters in Dentistry, Hina was extremely excited to start this new phase of her career with international exposure and couldn't wait till the end of the month to book her flight to ____."

The correct answer, of course, is Germany, arriving at which would require you to understand the importance of the term "German", which appears at the beginning of the sentence, on the outcome at the end of the sentence. This is another example of long-range dependence. The following figure shows the long-range dependence of the answer, "Germany&quot...