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

A student dropout prediction

In Chapter 3, Linear Regression with TensorFlow, you began your journey using TensorFlow to build a salary prediction model. Your boss was impressed, and now that you are fully settled in the data team, your manager wants you to work with a new client. Your job is to help them build a model that will predict whether a student will drop out of university or not, as this will help them support such students, thus preventing them from dropping out of school. Your manager has given you authorization and the task is now yours. For this task, historical data was made available to you by your client. Just like in Chapter 3, Linear Regression with TensorFlow, you had a rewarding chat with the client, and you identified the task as a binary classification problem. Let’s open the notebook labeled Classification with TensorFlow from the GitHub repository and get started.

Loading the data

Let’s start by loading the historical data that we received...