AI Powered Deep Learning Projects: Implementation with TensorFlow
Learning Path | 4 Course Series

Synopsis

Description

Tensorflow is the world's most popular library for deep learning, and it's built by Google, whose parent Alphabet recently became the most cash-rich company in the world (just a few days before I wrote this). It is the library of choice for many companies doing AI and machine learning. In other words, if you want to do deep learning, you gotta know Tensorflow. Deep Learning is one of the most popular fields in computer science today. It has applications in many and very varied domains. With the publishing of much more efficient deep learning models in the early 2010s, we have seen a great improvement in the state of the art in domains like Computer Vision, Natural Language Processing, Image Generation, and Signal Processing. The demand for Deep Learning engineers is skyrocketing and experts in this field are highly paid, because of their value. However, getting started in this field isn’t easy. There’s so much information out there, much of which is outdated and many times don't take the beginners into consideration. In this course, we shall take you on an amazing journey in which you'll master different concepts with a step-by-step and project-based approach. You shall be using Tensorflow (the world's most popular library for deep learning, and built by Google).

Deep Learning: Neural Networks with TensorFlow (3h 11m): Embark on a journey through the intricate world of neural networks with TensorFlow in this comprehensive course. Beginning with foundational concepts, you'll explore the architecture of neural networks, the significance of activation functions, and strategies for optimizing model performance. Through practical demonstrations and exercises, you'll implement neural networks for various tasks, including classification and regression, gaining proficiency in TensorFlow along the way.

Deep Learning: Automatic Image Captioning (2h 23m): Delve into the cutting-edge field of automatic image captioning in this engaging course. You'll unravel the underlying principles behind image captioning models and learn how to leverage deep learning frameworks to generate descriptive captions for images automatically. Through a blend of theory and hands-on projects, you'll dive deep into convolutional neural networks (CNNs) and recurrent neural networks (RNNs), mastering techniques for generating meaningful captions that capture the essence of visual content.

Project on TensorFlow: Face Mask Detection (33m): Put your deep learning skills into practice with this hands-on project focusing on face mask detection using TensorFlow. Guided by expert instructors, you'll learn how to develop a robust face mask detection system using convolutional neural networks (CNNs). By the end of the project, you'll have gained valuable experience in image classification and object detection, equipped to tackle real-world challenges in computer vision applications.

Project on TensorFlow - Implementing Linear Regression (1h 46m): Solidify your understanding of linear regression models by implementing them using TensorFlow in this project-based course. Starting with the basics of linear regression, you'll progress to building, training, and evaluating models using TensorFlow's powerful APIs. Through hands-on exercises and guided tutorials, you'll gain practical insights into implementing linear regression models efficiently, setting the stage for more complex deep learning projects.

Throughout these courses and projects, you'll not only acquire theoretical knowledge but also develop practical skills in deep learning, enabling you to tackle real-world problems and drive innovation in AI-powered solutions. Whether you're a novice or an experienced practitioner, these resources offer valuable insights and practical experience to advance your deep learning journey.

Course Ratings