TensorFlow Developer Certificate Guide: Efficiently tackle deep learning and ML problems to ace the Developer Certificate exam

by Oluwole Fagbohun

Overview

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.

Product Details

ISBN-13:	9781803249209
Publisher:	Packt Publishing
Publication date:	09/29/2023
Sold by:	Barnes & Noble
Format:	eBook
Pages:	344
File size:	13 MB
Note:	This product may take a few minutes to download.

About the Author

Oluwole Fagbohun, a certified TensorFlow developer and machine learning engineer, currently he is serving Vice President of Engineering and Environmental Data at ChangeBlock, where he is spearheading the fight against climate change with machine learning. Beyond his role at ChangeBlock, Oluwole is the founder of Readrly an EdTech startup employing AI to enhance children's reading skills, offering engaging and gamified learning experiences.

Table of Contents

Table of Contents

1. Introduction to Machine Learning
2. Introduction to Tensorflow
3. Linear Regression with Tensorflow
4. Classification with Tensorflow
5. Image Classification with Neural Networks
6. Improving the model
7. Image Classification with Convolution Neural Networks
8. Handling Overfitting
9. Transfer Learning
10. Introduction to Natural Language Processing
11. Natural Language Processing with Tensorflow
12. Introduction to Time Series, Sequence and Prediction
13. Time Series, Sequence and Prediction with Tensorflow