TensorFlow has been gaining immense popularity over the past few months, owing to its power and ease of use. This video aims to help you leverage the power of TensorFlow to perform image processing. Beginning with an introduction to image processing, the video will take you through TensorFlow's API-like graph tensor, which can be used for image classification.
Starting off with basic 2D images, the video will gradually take you through recognizing more complex images, colors, shapes, and so on. Making use of the Python API, you will move on to classifying and training your model to identify more complex images such as face and expression detection, while you will also perform classification using regression.
Then you will delve into more advanced stuff such as semantic segmentation, Neural Image Caption Generation, and so on, taking advantage of TensorFlow's Deep Neural Networks. Then the video will up the ante and cover advanced topics such as Object Tracking, Video stream processing, and, finally, accelerating image processing with a GPU.
About the author
Marvin Bertin has authored online Deep Learning courses. Marvin is the technical editor of a deep learning book and a conference speaker. He has a bachelor’s degree in Mechanical Engineering and Masters in Data Science.
Marvin has worked at a deep learning start-up developing neural network architectures. He is currently working in the biotech industry building NLP machine learning solutions. At the forefront of next generation DNA sequencing, he builds intelligent applications with Machine Learning and Deep Learning for precision medicine.
In this video, we are going to install package dependency manger with Miniconda, TensorFlow, and its dependencies. We will then launch the Jupyter Notebook.
In this video, we are going to learn about the Loss function in context of deep learning.
In this video, we are going to master in evaluation metrics and implement them in TensorFlow-Keras.
In this video, we are going to look at optimizers in deep learning.
In this video, you will understand more about TensorFlowKeras layer.
TensorFlow-Keras Functional API
In this video, we are going to look at the how to create Image Preprocessing methods and augmentation techniques for deep learning models.
In this video, we will explore the cat and dog dataset.
In this video, we will discuss the VGG network architecture.
In this video, we will go over the implementation of the VGG architecture.
In this video, we will train and evaluate the CIFAR-10 dataset.
In this video, we will learn about feature extraction.
In this video, we will cover another method of transfer learning called fine tuning.
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