Udemy – Convolutional Neural Networks with TensorFlow in Python 2021-3

Udemy – Convolutional Neural Networks with TensorFlow in Python 2021-3 Downloadly IRSpace

Apr 17, 2025 - 20:33 Updated: Apr 21, 2025 - 10:41

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Udemy – Convolutional Neural Networks with TensorFlow in Python 2021-3

Convolutional Neural Networks with TensorFlow in Python, This course is a fantastic training opportunity to help you gain insights into the rapidly expanding field of Machine Learning and Computer Vision through the use of Convolutional Neural Networks. Convolutional Neural Networks, or CNNs in short, are a subtype of deep neural networks that are extensively used in the field of Computer Vision. These networks specialize in inferring information from spatial-structure data to help computers gain high-level understanding from digital images and videos. That can be as simple a task as classifying an image to be a dog or a cat, but it can also explode in complexity as is the case with self-driving cars, for example. This is where most of the active Machine Learning research is concentrated right now, and CNNs are a crucial part of it. So, it is high time to up your game and master this piece of the Deep Learning puzzle. To do just that, we have devised this wonderful and engaging course for you.

Although a general understanding of TensorFlow and the main deep learning concepts is required, we will start from the CNNs basics and build our way to proficiency. Moreover, we are firm believers that practice makes perfect, that’s why this course offers a comprehensive practical example of a real-world project. What’s more, it contains plenty of exercises, homework, downloadable files and notebooks, as well as quiz questions and course notes. We’ll start this course by taking a look at Kernels in the context of image processing. Kernels are an essential tool for working with and understanding Convolutional Neural Networks. We’ll explore how to achieve different image transformations and help you understand the role of the mathematical operation of convolution in this process. This will be the basis for our next topic – convolutional layers.

What you’ll learn

Learn the fundamentals of Convolutional Neural Networks
Perform Computer Vision and Machine Learning tasks
Master working with TensorFlow and Tensorboard
Understand kernels
Get the hang of convolution and its role in CNNs
Get familiar with L2 regularization and weight decay
Grasp the concept of dropout
Visualize networks and metrics using Tensorboard
Approach multilabel classification

Who this course is for

Anyone seeking to advance their skills in Machine Learning and Computer Vision
This course is for you if you want to learn how Convolutional Neural Networks work
Anyone who wants to make a career in Deep Learning
Individuals who are curious and passionate about AI