Deep Learning courses

591 Courses

AWS Skill Builder

Exam Prep Official Pretest: AWS Certified Machine Learning Engineer - Associate (MLA-C01 - English)

Exam Prep Official Pretest: AWS Certified Machine Learning Engineer - Associate (MLA-C01 - English) The Exam Prep Official Pretest: AWS Certified Machine Learning Engineer - Associate (MLA-C01 - English) includes 65 questions and has a time limit of 130 minutes. This pretest aligns with the MLA-C01 version of the exam and exam guide. About AWS Ce.

PyTorch for Deep Learning

PyTorch for Deep Learning Learn PyTorch and become a proficient Deep Learning Engineer. This PyTorch course is a step-by-step guide designed to help you develop your own deep learning models. The curriculum includes essential topics such as Computer Vision, Neural Networks, and much more.

AWS Skill Builder

AWS ML Engineer Associate Curriculum Overview (Simplified Chinese)

AWS ML Engineer Associate Curriculum Overview (Simplified Chinese) 在这个 AWS ML Engineer Associate Curriculum 的入门课程中，您将回顾机器学习 (ML) 基础知识并研究 ML 和 AI 的演变。您将探索 ML 生命周期的初始步骤，确定业务目标并根据该业务目标制定 ML 问题。最后，您将了解 Amazon SageMaker，这是一项完全托管式 AWS 服务，可用于.

Coursera

Intel® Technical Pro – Principles of AI Software & Ecosystem

Intel® Technical Pro – Principles of AI Software & Ecosystem In the era of AI everywhere, businesses are reimagining every aspect of their operations, from finance to compliance, to see how AI can augment and automate workflows. Intel is helping businesses think differently about their enterprise AI strategies from the client to the edge to the.

Coursera

Intel® Solutions Pro – Principles of AI Everywhere

Intel® Solutions Pro – Principles of AI Everywhere AI is transforming how we work and live every day, and it is evolving rapidly. Intel is delivering a full spectrum of hardware and software platforms, offering open and modular solutions to expedite time-to-value in this era of exponential growth. Intel integrates AI seamlessly across its hardwar.

Udacity

AWS Machine Learning Engineer Nanodegree

AWS Machine Learning Engineer Nanodegree AWS Machine Learning Engineer Nanodegree The AWS Machine Learning Engineer (MLE) Nanodegree program aims to empower software developers and data scientists with essential data science and machine learning skills. This program emphasizes the construction and deployment of machine learning.

Udacity

Deep Learning

Udacity

Computer Vision

Computer Vision - Udacity Master the computer vision skills behind advances in robotics and automation. Write programs to analyze images, implement feature extraction, and recognize objects using deep learning models. University: Provider: Udacity Categories: Robotics Courses, Computer Vision Courses, Deep Learning Courses, Neural Networks Course.

Udacity

AI for Trading

AI for Trading | Udacity Complete real-world projects designed by industry experts, covering topics from asset management to trading signal generation. Master AI algorithms for trading, and build your career-ready portfolio. University: Provider: Udacity Categories: Artificial Intelligence Courses Python Courses Machine Learning Courses.

Udacity

Self Driving Car Engineer

Self Driving Car Engineer Work on the future of autonomous vehicles and help make the self-driving car revolution a reality! University: Provider: Udacity Categories: Machine Learning Courses, Computer Vision Courses, Deep Learning Courses, Autonomous Vehicles Courses, Kalman Filter Courses, Image Processing Courses, Localization Courses, PID C.

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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!