This is the code repository for TensorFlow Developer Certificate Guide, published by Packt.
Efficiently tackle deep learning and ML problems to ace the Developer Certificate exam
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.
This book covers the following exciting features:
- Prepare for success in the TensorFlow Developer Certification exam
- Master regression and classification modelling with TensorFlow 2.x
- Build, train, evaluate, and fine-tune deep learning models
- Combat overfitting using techniques such as dropout and data augmentation
- Classify images, encompassing preprocessing and image data augmentation
- Apply TensorFlow for NLP tasks like text classification and generation
- Predict time series data, such as stock prices
- Explore real-world case studies and engage in hands-on exercises
If you feel this book is for you, get your copy today!
All of the code is organized into folders.
The code will look like the following:
import numpy as np
from numpy import
Following is what you need for this book: This book is for machine learning and data science enthusiasts, as well as data professionals aiming to demonstrate their expertise in building deep learning applications with TensorFlow. Through a comprehensive hands-on approach, this book covers all the essential exam prerequisites to equip you with the skills needed to excel as a TensorFlow developer and advance your career in machine learning. A fundamental grasp of Python programming is the only prerequisite.
With the following software and hardware list you can run all code files present in the book (Chapter 1-13).
| Chapter | Software required | OS required |
|---|---|---|
| 1-13 | Python 3.9.2 | Windows, Mac OS X, and Linux (Any) |
| 1-13 | tensorflow==2.13.0 | Windows, Mac OS X, and Linux (Any) |
| 1-13 | numpy==1.24.3 | Windows, Mac OS X, and Linux (Any) |
| 1-13 | pandas==2.0.3 | Windows, Mac OS X, and Linux (Any) |
| 1-13 | Pillow==10.0.0 | Windows, Mac OS X, and Linux (Any) |
| 1-13 | scipy==1.10.1 | Windows, Mac OS X, and Linux (Any) |
| 1-13 | tensorflow-datasets==4.9.2 | Windows, Mac OS X, and Linux (Any) |
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.