8 lectures to help understand machine learning and neural networks

We have collected interesting lectures that will help us understand how machine learning works, what tasks it solves and what we can expect in the near future from machines that can learn. The first lecture is designed more likely for those who do not understand how machine learning works, in the rest there are many interesting cases.

Machine learning

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Introductory lecture from the candidate of physical and mathematical sciences Dmitry Vetrov. The scientist explains how machine learning works, what depth learning is and how neural networks are arranged.

Mathematical methods for forecasting sales

Another lecture from PostScience - member of the Russian Academy of Sciences Konstantin Vorontsov shows a particular example of the application of machine learning methods in business. The mathematician explains how his team built a sales forecasting model for a large retail chain.

The wonderful and terrible consequences of self-learning computers

TED speaker, machine learning specialist and Enlitic CEO Jeremy Howard makes his predictions about what will happen when we teach computers to learn.

How do we teach computers to understand images

Another lecture at TED. Computer vision expert Fay-Fey Lee describes the latest machine learning achievements, including a database of 15 million photos, which her team created to teach a computer to understand images.

How do we teach the technique not to watch and listen, but to see and hear?

Despite the first 20 minutes of silence, a rather vigorous lecture on in-depth training from the KL10CH technical hub and an engineer in machine learning, computer vision and signal processing at the Samsung Research Center Dmitry Korobchenko. For the most persistent and advanced.

And a bonus for those who are serious:

Recent Developments in Deep Learning

Lecture by renowned specialist in artificial neural networks Jeffrey Hinton, delivered at the University of Toronto. Professor Hinton talks about the main achievements in the field of deep learning.

Deep Learning, Self-Taught Learning and Unsupervised Feature Learning

One of the founders of Coursera, an associate professor at Stanford and an expert in machine learning and robotics, Andrew Eun, explains the intricacies of learning with and without a teacher.

Machine learning for video games

In five minutes, using the example of Mario, they will tell you how machine learning is used in the development of video games.