Advanced Machine Learning Specialization

开始时间: 04/23/2018 持续时间: Unknown

所在平台: Coursera专项课程

课程类别: 计算机科学

大学或机构: CourseraNew



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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.


7 courses

Introduction to Deep Learning
Upcoming session: Apr 23
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 st

How to Win a Data Science Competition: Learn from Top Kagglers
Upcoming session: Apr 23
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

Bayesian Methods for Machine Learning
Upcoming session: Apr 23
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 all

Natural Language Processing
Upcoming session: Apr 23
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-d

Practical Reinforcement Learning
Starts May 2018
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!

Deep Learning in Computer Vision
Starts May 3, 2018
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.

Addressing Large Hadron Collider Challenges by Machine Learning
Starts May 2018
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.



金_木水火土 2018-02-26 21:38 0 票支持; 0 票反对


Deep Learning Specialization on Coursera


俄罗斯国立高等经济学院和Yandex联合推出的高级机器学习专项课程系列(Advanced Machine Learning Specialization),该系列授课语言为英语,包括深度学习,Kaggle数据科学竞赛,机器学习中的贝叶斯方法,强化学习,计算机视觉,自然语言处理等7门子课程,截止目前前4门课程已开,感兴趣的同学可以关注: Deep Dive Into The Modern AI Techniques-You will teach computer to see, draw, read, talk, play games and solve industry problems.


机器学习 高级机器学习 高级机器学习专项课程 深度学习 强化学习 计算机视觉 自然语言处理 Kaggle 数据科学 数据科学竞赛 Kaggle竞赛 贝叶斯方法