Convolutional Neural Networks with TensorFlow in Python

Are you a Deep Learning enthusiast who is now looking for their next challenge. Are you interested in the field of Computer Vision and the ability of machines to extract insightful information from visuals and images. Do you want to learn a valuable skill to put yourself ahead of the competition in this AI-driven world.

If you answered with "yes" to any of these questions, you have come to the right place and at the right time. Here are 5 reasons this is the right course for you:We have 1,170,000 students on Udemy and we know how to teach a complex topic in an easy to understand wayIt contains numerous practical exercisesA real-life case study with 16,000 imagesSave time - our course will get you there faster than the average courses on the topicNotebook files, course notes, quiz questions, practice materials - all materials are inside the courseThis 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.