| Books and Resources | Status of Completion |
|---|---|
| 1. Deep Learning for Computer Vision with Python |
| Projects and Notebooks |
|---|
| 1. Image Classification |
Day1 of MachineLearningDeepLearning
- On my Journey of Machine Learning and Deep Learning, I have been reading about History of Deep Learning, Image Fundamentals, Pixels, Scaling and Aspect Ratios, Image Classification, Semantic Gap, Feature Extraction, Viewpoint Variation, Scale Variation, Deformation, Occlusions, Illumination, Background Clutter, Intra-class Variation, Supervised and Unsupervised Learning and few more topics related to the same. I have presented the notes about Image Classification, Semantic Gap, Feature Extraction, Supervised and Unsupervised Learning here in the snapshot. I hope you will also spend some time learning the topics from the Book mentioned below. Excited about the days ahead !!
- Book:
- Deep Learning for Computer Vision with Python
Day2 of MachineLearningDeepLearning
- On my Journey of Machine Learning and Deep Learning, I have been reading the book Deep Learning for Computer Vision with Python. Here, I have read about Image Classification, OpenCV, Animals Dataset, Raw Pixel Intensities, Convolutional Neural Networks, Dataset Loader and Preprocessing Modules, Aspect Ratio, Resizing and Scaling and few more topics related to the same from here. I have presented the implementation of Image Preprocessor and Dataset Loader here in the snapshot. I hope you will gain some insights and work on the same. I hope you will also spend some time learning the topics from the Book mentioned below. Excited about the days ahead !!
- Book:
- Deep Learning for Computer Vision with Python
- Image Classification
