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

Introduction to transfer learning

As humans, it is easy for us to transfer knowledge gained from one task or activity to another. For instance, if you have a good grasp of Python (the programming language, not the snake) and you decide to learn Rust, because of your background knowledge in Python, you will find it easier to learn Rust compared to someone who has never written a basic program in any programming language. This is because certain concepts, such as object-oriented programming, have similarities across different programming languages. Transfer learning follows the same principle.

Transfer learning is a technique in which we leverage a model pre-trained on task A to solve a different but related task B. For example, we use a neural network trained on one task and transfer the knowledge gained to multiple related tasks. In image classification, we often use deep learning models that have been trained on very large datasets, such as ImageNet, which is made up of more than...