Deep Learning courses

488 Courses

Udemy

Master Computer Vision™ OpenCV4 in Python with Deep Learning

Develop your computer vision expertise with the "Master Computer Vision™ OpenCV4 in Python with Deep Learning" course. Dive into the world of OpenCV4 and enhance your skills in Dlib and deep learning using Keras, TensorFlow, and Caffe. This comprehensive program offers you 21 real-life projects that bolster your understanding and application of.

Udemy

Neural Networks in Python: Deep Learning for Beginners

Embark on your journey into the world of Artificial Neural Networks with our comprehensive beginner's course, "Neural Networks in Python: Deep Learning for Beginners." Designed for aspiring data scientists and AI enthusiasts, this course will guide you through the fundamentals of neural networks using Python. Throughout this course, you will le.

Udemy

Deep Learning: Convolutional Neural Networks in Python

Embark on a comprehensive journey into the realm of Deep Learning with our course on Convolutional Neural Networks (CNNs) using Python. Dive into TensorFlow 2 and empower your skills in fields such as Computer Vision and Natural Language Processing (NLP). Ideal for those interested in Data Science and Machine Learning, this course will enhance y.

Udemy

Deep Learning with TensorFlow 2.0

Advance your technical skills with our specialised course on Deep Learning with TensorFlow 2.0. This course offers a comprehensive guide to building sophisticated deep learning algorithms, immersing you in the world of neural networks. Learn from Udemy's seasoned instructors through hands-on projects and real-world business case applications..

Udemy

Generative AI, from GANs to CLIP, with Python and Pytorch

Expand your knowledge and skills in artificial intelligence by diving into the world of generative models. Our Udemy course, "Generative AI, from GANs to CLIP, with Python and Pytorch," offers a comprehensive guide to understanding and implementing cutting-edge AI architectures. Designed for those passionate about AI development, this course.

Udemy

The Data Science Course: Complete Data Science Bootcamp 2024

Discover a complete training path in Data Science with the Data Science Bootcamp 2024 offered by Udemy. This extensive course covers essential topics from basic mathematics and statistics to advanced concepts in Python programming, machine learning, and deep learning. Whether you're starting your journey in data science or looking to.

Udemy

Deep Learning Python Project: CNN based Image Classification

Embark on a transformative journey into the world of deep learning with our comprehensive project on image classification using Convolutional Neural Networks (CNN). Designed for beginners, this course utilizes the CIFAR-10 dataset and provides detailed insights into building and training your own CNN models leveraging Python's powerful framewor.

XuetangX

Intelligent Control（智能控制）

The rise and in-depth research of artificial intelligence propel control theory toward simulating various intelligences. Concurrently, the automatic control of unmanned systems and intelligent products drives continuous development in intelligent control technology. This course serves as a professional core for students majoring in automation, c.

Udemy

【試験対策から本質の理解まで、知識をまとめて身に付けよう！】G検定対策講座

イベントタイトル：試験対策から本質の理解まで、知識をまとめて身に付けよう！G検定対策講座概要：G検定は機械学習やディープラーニングの基礎を学ぶための重要な入口となる試験です。この講座では、受験対策として知識をまとめ、本質的な理解を深められるようにサポートします。プラットフォーム：Udemy 関連カテゴリー：人工知能コース、機械学習コース、ディープラー.

Udemy

All of AI: ChatGPT, Midjourney, Stable Diffusion & App Dev

Find this AI course on Udemy Explore various aspects of artificial intelligence, from ChatGPT and prompt engineering to OpenAI API and beyond. This course covers diverse topics such as AI app development, chatbots, GPTs, and machine learning. Get hands-on experience with generative AI, automation, and copilot functionalities. Perfect for anyon.

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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!