Deep Learning courses

591 Courses

DataCamp

Data Skills for Business

Join the 'Data Skills for Business' course by DataCamp and enrich your knowledge in core data concepts. Equip yourself with the skills to answer real-world questions using data and enhance your ability as a data-driven decision-maker within your organization. Data is an invaluable resource in the modern world, making it essential to comprehend a.

Coursera

Deep Learning Frameworks and Neural Networks Simplified

Join our comprehensive Deep Learning program and equip yourself with advanced skills in TensorFlow, Keras, Recurrent Neural Networks (RNNs), and Neural Networks. Learn to implement cutting-edge AI models and frameworks to effectively tackle real-world challenges and drive impactful innovations. Master TensorFlow and Keras: Discover Tenso.

Coursera

AI & Deep Learning Concepts and Applications

Embark on a journey to master the intricacies of Artificial Intelligence and Deep Learning with our program designed to instill essential knowledge and practical prowess. You will comprehensively explore AI fundamentals, machine learning methodologies, and deep learning tools to address complex issues and spark innovation. Master AI Fundam.

AWS Skill Builder

Fundamentals of Machine Learning and Artificial Intelligence (日本語)

Fundamentals of Machine Learning and Artificial Intelligence (日本語) - AWS Skill Builder このコースでは、機械学習 (ML) と人工知能 (AI) の基礎について学びます。AI、ML、深層学習、そして生成人工知能 (生成 AI) という新たな分野の関係を探ります。基本的な AI 用語をしっかりと理解し、これらの概念をより深く掘り下げるための基礎を築きます。さらに、AI と ML.

Udemy

Harnessing AI and Machine Learning for Geospatial Analysis

Explore the fascinating world of artificial intelligence and machine learning as applied to geospatial analysis through our expertly crafted course. Enhance your skills in AI, deep learning, and machine learning techniques tailored for geospatial data. Offered by Udemy, this course dives deep into the intersection of these cutting-edge technol.

AWS Skill Builder

Fundamentals of Machine Learning and Artificial Intelligence (简体中文)

在本课程中，您将学习机器学习 (ML) 和人工智能 (AI) 的基础知识。您将探索 AI、ML、深度学习和新兴的生成式人工智能领域之间的联系，充分理解 AI 的基础术语，为深入探究奠定基础。此外，您将了解使用 AI 和 ML 功能的精选 Amazon Web Services (AWS) 服务，并获得关于如何使用这些工具解决现实问题和推动各行业创新的实用见解。课程级别：基础级时长：1 小时.

AWS Skill Builder

Fundamentals of Machine Learning and Artificial Intelligence (한국어)

In this course, you'll delve into the fundamentals of Machine Learning (ML) and Artificial Intelligence, examining the relationships among AI, ML, deep learning, and emerging generative AI. You'll solidify your understanding of essential AI terms, setting a foundation for deeper exploration. Additionally, you'll learn about how different AWS s.

Udemy

ChatGPT Secrets | ChatGPT Mastery | ChatGPT Masterclass

AWS Skill Builder

Fundamentals of Machine Learning and Artificial Intelligence (Bahasa Indonesia)

Dalam kursus ini, Anda akan belajar tentang dasar-dasar machine learning (ML) dan kecerdasan buatan (AI). Anda akan melihat berbagai bentuk hubungan antara AI, ML, deep learning, dan bidang kecerdasan buatan generatif yang sedang berkembang (AI generatif). Anda akan mendapatkan pemahaman yang sangat baik tentang istilah AI dasar, sehingga me.

Udemy

Practical Machine Learning for Data Scientists

Embark on a journey into the world of Artificial Intelligence with Udemy's Practical Machine Learning for Data Scientists course. Whether you're diving into AI for the first time or looking to sharpen your skills, this course provides a solid foundation in practical AI and ML techniques. Learn from Udemy - a leader in online education - and ga.

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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!