StatLearning: Statistical Learning (Stanford Online) 3 个评论 关注

主页: https://class.stanford.edu/courses/HumanitiesScience/StatLearning/Winter2014/about

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CVX101: Convex Optimization (Stanford Online) 1 个评论 关注

主页: https://class.stanford.edu/courses/Engineering/CVX101/Winter2014/about

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Analytic Combinatorics (CourseraArchive) 0 个评论 关注

主页: https://www.coursera.org/course/ac

简介: Analytic Combinatorics teaches a calculus that enables precise quantitative predictions of large combinatorial structures. This course introduces the symbolic method to derive functional relations among ordinary, exponential, and multivariate generating functions, and methods in complex analysis for deriving accurate asymptotics from the GF equations.

Statistical Analysis of fMRI Data (CourseraArchive) 1 个评论 关注

主页: https://www.coursera.org/course/fmri

简介: Explore the intersection of statistics and functional magnetic resonance imaging (fMRI), a non-invasive technique for studying brain activity.

Introduction to Probability - The Science of Uncertainty (EdxArchive) 3 个评论 关注

主页: https://www.edx.org/archive/introduction-probability-science-mitx-6-041x-0

简介: An introduction to probabilistic models, including random processes and the basic elements of statistical inference.

Neural Networks for Machine Learning (CourseraArchive) 5 个评论 关注

主页: https://www.coursera.org/course/neuralnets

简介: Learn about artificial neural networks and how they're being used for machine learning, as applied to speech and object recognition, image segmentation, modeling language and human motion, etc. We'll emphasize both the basic algorithms and the practical tricks needed to get them to work well.

機器學習基石 (Machine Learning Foundations) (CourseraArchive) 10 个评论 关注

主页: https://www.coursera.org/course/ntumlone

简介: Machine learning is the study that allows computers to adaptively improve their performance with experience accumulated from the data observed. The course teaches the most fundamental algorithmic, theoretical and practical tools that any user of machine learning needs to know. [機器學習旨在讓電腦能由資料中累積的經驗來自我進步。本課程將介紹各領域中的機器學習使用者都應該知道的基礎演算法、理論及實務工具。]

Mining Massive Datasets (CourseraArchive) 1 个评论 关注

主页: https://www.coursera.org/course/mmds

简介: This class teaches algorithms for extracting models and other information from very large amounts of data. The emphasis is on techniques that are efficient and that scale well.

Data Analysis and Statistical Inference (CourseraArchive) 1 个评论 关注

主页: https://www.coursera.org/course/statistics

简介: This course introduces you to the discipline of statistics as a science of understanding and analyzing data. You will learn how to effectively make use of data in the face of uncertainty: how to collect data, how to analyze data, and how to use data to make inferences and conclusions about real world phenomena.

Introduction to Hadoop and MapReduce (Udacity) 1 个评论 关注

主页: https://www.udacity.com/course/ud617

简介: The Apache™ Hadoop® project develops open-source software for reliable, scalable, distributed computing. Learn the fundamental principles behind it, and how you can use its power to make sense of your Big Data.