A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
Thank you for your great repository and book. First of all, I should say that your book is one of the best in the field of machine learning. I have studied your book and reviewed your codes. I found that in Chapter 14, particularly in the classification and localization section, there are no annotated images. To address this, I created a dataset that might be useful for your code.
In this work, I downloaded and processed 550 images of flowers from the TDFS.flowers dataset using VGG Image Annotator for feature extraction. This dataset is used to train a model designed to detect the location of flowers within images. I employed an Xception-based architecture as the backbone of the detection model.
Dear auther,
Thank you for your great repository and book. First of all, I should say that your book is one of the best in the field of machine learning. I have studied your book and reviewed your codes. I found that in Chapter 14, particularly in the classification and localization section, there are no annotated images. To address this, I created a dataset that might be useful for your code.
In this work, I downloaded and processed 550 images of flowers from the TDFS.flowers dataset using VGG Image Annotator for feature extraction. This dataset is used to train a model designed to detect the location of flowers within images. I employed an Xception-based architecture as the backbone of the detection model.
Thanks, Shayan Dodge