Book Image

TensorFlow Developer Certificate Guide

By : Oluwole Fagbohun
4 (2)
Book Image

TensorFlow Developer Certificate Guide

4 (2)
By: Oluwole Fagbohun

Overview of this book

The TensorFlow Developer Certificate Guide is an indispensable resource for machine learning enthusiasts and data professionals seeking to master TensorFlow and validate their skills by earning the certification. This practical guide equips you with the skills and knowledge necessary to build robust deep learning models that effectively tackle real-world challenges across diverse industries. You’ll embark on a journey of skill acquisition through easy-to-follow, step-by-step explanations and practical examples, mastering the craft of building sophisticated models using TensorFlow 2.x and overcoming common hurdles such as overfitting and data augmentation. With this book, you’ll discover a wide range of practical applications, including computer vision, natural language processing, and time series prediction. To prepare you for the TensorFlow Developer Certificate exam, it offers comprehensive coverage of exam topics, including image classification, natural language processing (NLP), and time series analysis. With the TensorFlow certification, you’ll be primed to tackle a broad spectrum of business problems and advance your career in the exciting field of machine learning. Whether you are a novice or an experienced developer, this guide will propel you to achieve your aspirations and become a highly skilled TensorFlow professional.
Table of Contents (20 chapters)
1
Part 1 – Introduction to TensorFlow
6
Part 2 – Image Classification with TensorFlow
12
Part 3 – Natural Language Processing with TensorFlow
15
Part 4 – Time Series with TensorFlow

Text preprocessing

NLP is an exciting and evolving field that lies at the intersection of computer science and linguistics. It empowers computers with the ability to understand, analyze, interpret, and generate text data. However, working with text data presents a unique set of challenges, one that differs from the tabular and image data we worked with in the earlier sections of this book. Figure 10.1 gives us a high-level overview of some of the inherent challenges that text data presents. Let’s drill into them and see what and how they present issues to us when building deep learning models with text data.

Figure 10.1 – The challenges presented by text data

Figure 10.1 – The challenges presented by text data

Text data in its natural form is unstructured, and this is just the beginning of the uniqueness of this interesting type of data we will work with in this chapter. Let's illustrate some of the issues by looking at these two sentences – “The house next to ours is beautiful...