Book Image

TensorFlow Developer Certificate Guide

By : Oluwole Fagbohun
3 (1)
Book Image

TensorFlow Developer Certificate Guide

3 (1)
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

Retail store forecasting

Imagine you are working as a machine learning engineer and your company just landed a new project. A rapidly growing superstore in Florida wants your help. They want to predict future reviews, as this will serve as a guide in planning the expansion of their stores to meet the expected demand. You have been saddled with the responsibility of building a forecasting model with the available historical data provided by the Tensor superstore. Let’s jump in and see how you can solve this problem, as your company is counting on you. Let’s get started!

  1. We begin by importing the necessary libraries for our project:
    import pandas as pd
    import numpy as np
    import matplotlib.pyplot as plt

    Here, we import numpy and matplotlib for numerical analysis and visualization purposes and pandas for data transformations.

  2. Next, we load the time series data:
    df = pd.read_csv('/content/sales_data.csv')
    df.head()

    Here, we load the data and use the head function...