Advanced Machine Learning 专项课程

Deep Dive Into The Modern AI Techniques。You will teach computer to see, draw, read, talk, play games and solve industry problems.

本专项课程介绍

This specialization gives an introduction to deep learning, reinforcement learning, natural language understanding, computer vision and Bayesian methods. Top Kaggle machine learning practitioners and CERN scientists will share their experience of solving real-world problems and help you to fill the gaps between theory and practice. Upon completion of 7 courses you will be able to apply modern machine learning methods in enterprise and understand the caveats of real-world data and settings.

制作方：

行业合作伙伴：

7 courses

按照建议的顺序或选择您自己的顺序。

项目

旨在帮助您实践和应用所学到的技能。

证书

在您的简历和领英中展示您的新技能。

项目概览

You will master your skills by solving a wide variety of real-world problems like image captioning and automatic game playing throughout the course projects. You will gain the hands-on experience of applying advanced machine learning techniques that provide the foundation to the current state-of-the art in AI.

课程

Advanced Specialization.: Designed for those already in the industry.

第 1 门课程
Introduction to Deep Learning
当前班次：Apr 23
课程学习时间
6 weeks of study, 6-10 hours/week
字幕
English
课程概述
The goal of this course is to give learners basic understanding of modern neural networks and their applications in computer vision and natural language understanding. The course starts with a recap of linear models and discussion of stoch
您可以选择只参加本课程。 了解更多。
第 2 门课程
How to Win a Data Science Competition: Learn from Top Kagglers
当前班次：Apr 23
课程学习时间
6-10 hours/week
字幕
English
课程概述
If you want to break into competitive data science, then this course is for you! Participating in predictive modelling competitions can help you gain practical experience, improve and harness your data modelling skills in various domains su
您可以选择只参加本课程。 了解更多。
第 3 门课程
Bayesian Methods for Machine Learning
当前班次：Apr 23
课程学习时间
6 weeks of study, 6 hours/week
字幕
English
课程概述
Bayesian methods are used in lots of fields: from game development to drug discovery. They give superpowers to many machine learning algorithms: handling missing data, extracting much more information from small datasets. Bayesian methods also allow
您可以选择只参加本课程。 了解更多。
第 4 门课程
Natural Language Processing
当前班次：Apr 23
课程学习时间
5 weeks of study, 4-5 hours per week
字幕
English
课程概述
This course covers a wide range of tasks in Natural Language Processing from basic to advanced: sentiment analysis, summarization, dialogue state tracking, to name a few. Upon completing, you will be able to recognize NLP tasks in your day-to-day
您可以选择只参加本课程。 了解更多。
第 5 门课程
Practical Reinforcement Learning
于 May 2018 开始
课程学习时间
6 weeks of study, 3-6 hours/week for base track, 6-9 with all the horrors of honors section
字幕
English
课程概述
Welcome to the Reinforcement Learning course. Here you will find out about: - foundations of RL methods: value/policy iteration, q-learning, policy gradient, etc. --- with math & batteries included - using deep neural networks for RL tasks --- also known as "the hype train" - state of the art RL algorithms --- and how to apply duct tape to them for practical problems. - and, of course, teaching your neural network to play games --- because that's what everyone thinks RL is about. We'll also use it for seq2seq and contextual bandits. Jump in. It's gonna be fun!
您可以选择只参加本课程。 了解更多。
第 6 门课程
Deep Learning in Computer Vision
于 May 3, 2018 开始
课程学习时间
5 weeks of study
字幕
English
课程概述
Deep learning added a huge boost to the already rapidly developing field of computer vision. With deep learning, a lot of new applications of computer vision techniques have been introduced and are now becoming parts of our everyday lives. These include face recognition and indexing, photo stylization or machine vision in self-driving cars. The goal of this course is to introduce students to computer vision, starting from basics and then turning to more modern deep learning models. We will cover both image and video recognition, including image classification and annotation, object recognition and image search, various object detection techniques, motion estimation, object tracking in video, human action recognition, and finally image stylization, editing and new image generation. In course project, students will learn how to build face recognition and manipulation system to understand the internal mechanics of this technology, probably the most renown and oftenly demonstrated in movies and TV-shows example of computer vision and AI.
您可以选择只参加本课程。 了解更多。
第 7 门课程
Addressing Large Hadron Collider Challenges by Machine Learning
于 May 2018 开始
课程学习时间
5 weeks of study
字幕
English
课程概述
The Large Hadron Collider (LHC) is the largest data generation machine for the time being. It doesn’t produce the big data, the data is gigantic. Just one of the four experiments generates thousands gigabytes per second. The intensity of data flow is only going to be increased over the time. So the data processing techniques have to be quite sophisticated and unique. In this course we’ll introduce students into the main concepts of the Physics behind those data flow so the main puzzles of the Universe Physicists are seeking answers for will be much more transparent. Of course we will scrutinize the major stages of the data processing pipelines, and focus on the role of the Machine Learning techniques for such tasks as track pattern recognition, particle identification, online real-time processing (triggers) and search for very rare decays. The assignments of this course will give you opportunity to apply your skills in the search for the New Physics using advanced data analysis techniques. Upon the completion of the course you will understand both the principles of the Experimental Physics and Machine Learning much better.
您可以选择只参加本课程。 了解更多。

制作方

Faculty of Computer Science (http://cs.hse.ru/en/) trains developers and researchers. The program was created based on the experience of leading American and European universities, such as Stanford University (U.S.) and EPFL (Switzerland). It is also closely related to Yandex School of Data Analysis, which is one of the strongest postgraduate schools in the field of computer science in Russia. In the faculty, learning is based on practice and projects.
National Research University - Higher School of Economics (HSE) is one of the top research universities in Russia. Established in 1992 to promote new research and teaching in economics and related disciplines, it now offers programs at all levels of university education across an extraordinary range of fields of study including business, sociology, cultural studies, philosophy, political science, international relations, law, Asian studies, media and communications, IT, mathematics, engineering, and more. Learn more on www.hse.ru