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 classification using the AG News dataset – 
a comparative study

The AG News dataset is a collection of more than 1 million news articles, collected from over 2,000 news sources by a news search engine called ComeToMyHead. The dataset is distributed across four categories – namely, world, sports, business, and science and technology – and it is available on TensorFlow Datasets (TFDS). The dataset is made up of 120,000 training samples (30,000 from each category), and the test set contains 7,600 examples.

Note

This experiment may take about an hour to run, due to the size of the dataset and the number of models; hence, it is important to ensure your notebook is GPU-enabled. Again, you could take a smaller subset to ensure your experiments run much faster.

Let’s start building our model:

  1. We will begin by loading the necessary libraries for this experiment:
    import pandas as pd
    import tensorflow_datasets as tfds
    import tensorflow as...