Book Image

Python Machine Learning Workbook for Beginners

By : AI Sciences
Book Image

Python Machine Learning Workbook for Beginners

By: AI Sciences

Overview of this book

<p>Machine Learning (ML) is the lifeblood of businesses worldwide. ML tools empower organizations to identify profitable opportunities fast and help them to better understand potential risks. The ever-expanding data, cost-effective data storage, and competitively priced powerful processing continue to drive the growth of ML. </p><p> </p><p>This is the best time you could enter the exciting machine learning universe. Industries are reinventing themselves constantly by developing more advanced data analysis models. These models analyze larger and more complex data than ever while delivering instantaneous and more accurate results on enormous scales. </p><p>In this backdrop, it is evident that hands-on practice is everything in machine learning. Tons of theory will amount to nothing if you don’t have enough hands-on practice. Textbooks and online classes mislead you into a false sense of mastery. The easy availability of learning resources tricks you and you become overconfident. But when you try to apply the theoretical concepts you have learned, you realize it’s not that simple. </p><p> </p><p>This is where projects play a crucial role in your learning journey. Projects are doubtless the best investment of your time. You’ll not only enjoy learning but you’ll also make quick progress. And unlike studying boring theoretical concepts, you’ll find that working on projects is easier to stay motivated. </p><p> </p><p>The projects in this book cover ten different interesting topics. Each project will help you refine your ML skills and apply them in the real world. These projects also present you with an opportunity to enrich your portfolio, making it simpler to find a great job, explore interesting career paths, and even negotiate a higher pay package. Overall, this learning-by-doing book will help you accomplish your machine learning career goals faster. </p><p> </p><p>The code bundle for this course is available at https://www.aispublishing.net/ai-sciences-book</p>
Table of Contents (15 chapters)
1
About the Author

6.2. Cats and Dogs Image Classification with a CNN

In this section, we will move forward with the implementation of the convolutional neural network in Python. We know that a convolutional neural network can learn to identify the related features on a 2D map, such as images. In this project, we will solve the image classification task with CNN. Given a set of images, the task is to predict whether an image contains a cat or a dog.

Importing the Dataset and Required Libraries

The dataset for this project consists of images of cats and dogs. The dataset can be downloaded directly from this Kaggle Link (https://www.kaggle.com/c/dogs-vs-cats).

The dataset is also available inside the Animal Datasets, which is located inside the Datasets folder in the GitHub and SharePoint repositories. The original dataset consists of 2,500 images. But the dataset that we are going to use will be smaller and will consist of 10,000 images. Out of 10,000 images, 8,000 images are used for training, while 2,000...