Deep Learning courses

635 Courses

Coursera

Computer Vision: YOLO Custom Object Detection with Colab GPU

Computer Vision: YOLO Custom Object Detection with Colab GPU In this comprehensive course, you'll dive into the world of real-time object detection with YOLO, one of the most powerful algorithms for detecting objects in images and videos. The course begins with an introduction to YOLO and object detection, followed by setting up your development.

Coursera

PyTorch Ultimate 2024 - From Basics to Cutting-Edge

PyTorch Ultimate 2024 - From Basics to Cutting-Edge Embark on a transformative learning experience with our PyTorch Ultimate 2024 course. Begin with a solid foundation, understanding the key topics and objectives, and seamlessly transition through machine learning essentials and deep learning principles. From setting up your environment to master.

Coursera

Advanced Chatbots with Deep Learning and Python

Advanced Chatbots with Deep Learning and Python This course is designed to equip learners with the knowledge and skills required to develop advanced chatbots using deep learning and Python. The initial modules provide an overview of chatbots, their evolution, and the benefits of incorporating AI into chatbot development. Learners wil.

Coursera

Chatbots for Beginners: A Complete Guide to Build Chatbots

Chatbots for Beginners: A Complete Guide to Build Chatbots Embark on a journey to master chatbot development with this detailed course designed for beginners. Starting with an introduction to chatbots, you’ll learn their history, applications, and benefits. Understand the differences between rule-based and self-lear.

Coursera

Advanced RNN Concepts and Projects

Advanced RNN Concepts and Projects This advanced course on Recurrent Neural Networks (RNNs) addresses key challenges like the vanishing gradient problem and provides solutions such as Gated Recurrent Units (GRUs) and Long Short Term Memory (LSTM) networks. You'll start with an overview of improved RNN modules and delve into bidirectional RNNs a.

Coursera

Keras Deep Learning & Generative Adversarial Networks (GAN)

Keras Deep Learning & Generative Adversarial Networks (GAN) This course is designed to take you on an in-depth journey through the world of deep learning and artificial intelligence. Beginning with an introduction to AI and machine learning concepts, you’ll build a solid foundation in neural networks and deep learning with the Keras framework. As.

Coursera

Advanced Generative Adversarial Networks (GANs)

Advanced Generative Adversarial Networks (GANs) Embark on an enlightening journey into the realm of Generative Adversarial Networks (GANs), where you will master the art of AI-driven image synthesis. This course begins with a solid foundation, introducing you to the basic concepts and components of GANs, such as the Generator and Discriminator..

Coursera

RNN Architecture and Sentiment Classification

Title: RNN Architecture and Sentiment Classification Description: Artificial Intelligence is revolutionizing data analysis. This course delves into Recurrent Neural Networks (RNNs), starting with basic memory models and advancing to deep RNN structures. You'll explore RNN models like ManyToMany, ManyToOne, and OneToMany through practical exerci.

Coursera

Johns Hopkins University

Mastering Neural Networks and Model Regularization

Mastering Neural Networks and Model Regularization The course "Mastering Neural Networks and Model Regularization" dives deep into the fundamentals and advanced techniques of neural networks, from understanding perceptron-based models to implementing cutting-edge convolutional neural networks (CNNs). This course offers hands-on experience with r.

Coursera

University of Pennsylvania

Deep Learning Essentials

Deep Learning Essentials | University of Pennsylvania | Coursera Join the University of Pennsylvania's Deep Learning Essentials course on Coursera. Delve into the rich history of deep learning, and gain a profound understanding of neural networks, including the perceptron. Discover how these networks function and explore the architectu.

Coursera

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What is deep learning?

“Deep learning” – literally “deep learning”. This is about artificial intelligence and increasing its abilities through training, based not on artificial codes, but on principles similar to the development of human intelligence. Deep learning methods make it possible to make machines self-learning.

The term itself and developments in this area appeared 40 years ago, but until 2012 they could not be applied in practice, as they were limited by insufficient technical capacity. Now there are already published works by the pioneers of deep learning, and textbooks and training courses in this specialty are gradually appearing.

Deep learning on your fingers: The ability of a machine to find an answer using calculations is called artificial intelligence. A machine can be taught to learn independently by building appropriate algorithms - this is called machine learning. With this approach, coded algorithms will no longer be needed to solve problems. The process of acquiring and using skills imitates human thinking and is called deep learning.

What tasks can be performed using deep learning right now?

If at the dawn of automation machines learned to do mechanical work for humans, now machines are learning to do routine intellectual work for us. The further progress we make, the more tasks we can shift to them, freeing up time for what really matters.

Officially, the main task of deep learning is the automation of complex tasks in various areas of human activity. It's like a computer, only of a different century and a different level.

But of particular interest is the neural network’s assistance in creating programs for solving cognitive problems.

Enough general phrases, let's move on to examples:

Face recognition by the DeepFace system is about 97%, and this result is about the same as that of the average person.

Imitation of human speech by the WaveNet system. This is not reading the text, but composing sentences with accents, without errors in stress and without unnatural pauses.

Making medical diagnoses. For example, determining diabetic retinopathy from photographs of the eyes. The technology is already being used in US medical institutions.

It’s hard to even imagine what awaits us in the future if people outside of IT have just heard about deep machine learning, and it has already produced such amazing results.

Why study deep learning?

To earn twice as much as ordinary IT specialists. Progress in the field of information technology is not just walking, but actually running, and it’s time to benefit from it. The sphere is not yet oversaturated, and oversaturation will not happen soon. Still, creating neural networks is not as simple as filing nails or maintaining Instagram accounts. But now is the time to start studying in order to develop along with your specialty and, perhaps, soon become someone who develops it.

Deep learning courses that currently exist are divided into four categories. Decide for yourself which one is for you:

Trainings are highly specialized classes for practicing specific skills. Suitable for those who need to form an understanding of the basic principles of machine thinking.

Long courses - for AI specialists and those involved in database analysis. Long-term deeplearning ai courses are not for everyone and require patience and time.

University programs - for maximum immersion in the subject. They may be too difficult for beginners, although the application of effort will give results that should not be expected from short courses.

A short best deep learning course on technology in business - general information for managers who will not be doing it themselves, but need to have an understanding of the subject.

You will have to put in a lot of effort, but the result is worth it. Just for fun, you can look at vacancies for deep learning specialists on sites with job offers and evaluate upcoming prospects. Not everyone needs deep learning experience yet, and soon all the sweet jobs will require several years of practice. So, if you have the ability to train soulless machines that are almost equal to us in intelligence, hurry up to take up vacant positions after a deep learning online course from AI Eeducation!