Algorithms, Part I (CourseraArchive) 6 个评论 关注

开始时间: 04/22/2022 持续时间: 6 weeks

主页: https://www.coursera.org/course/algs4partI

简介: This course covers the essential information that every serious programmer needs to know about algorithms and data structures, with emphasis on applications and scientific performance analysis of Java implementations. Part I covers basic iterable data types, sorting, and searching algorithms.

Machine Learning (CourseraArchive) 29 个评论 关注

开始时间: 04/22/2022 持续时间: Unknown

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

简介: Learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself.

Scientific Computing (CourseraArchive) 1 个评论 关注

开始时间: 04/22/2022 持续时间: 10 weeks

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

简介: Investigate the flexibility and power of project-oriented computational analysis, and enhance communication of information by creating visual representations of scientific data.

機器學習技法 (Machine Learning Techniques) (CourseraArchive) 2 个评论 关注

开始时间: 04/22/2022 持续时间: 8 weeks

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

简介: The course extends the fundamental tools in "Machine Learning Foundations" to powerful and practical models by three directions, which includes embedding numerous features, combining predictive features, and distilling hidden features. [這門課將先前「機器學習基石」課程中所學的基礎工具往三個方向延伸為強大而實用的工具。這三個方向包括嵌入大量的特徵、融合預測性的特徵、與萃取潛藏的特徵。]

Introduction to Natural Language Processing (CourseraArchive) 0 个评论 关注

开始时间: 04/22/2022 持续时间: 12 weeks

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

简介: This course provides an introduction to the field of Natural Language Processing, including topics like Parsing, Semantics, Question Answering, and Sentiment Analysis.

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

开始时间: 04/22/2022 持续时间: 8 weeks

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。]

Introduction to Big Data with Apache Spark (EdxArchive) 1 个评论 关注

开始时间: 04/22/2022 持续时间: 5 weeks

主页: https://www.edx.org/archive/introduction-big-data-apache-spark-uc-berkeleyx-cs100-1x

简介: Learn how to apply data science techniques using parallel programming in Apache Spark to explore big (and small) data.

Scalable Machine Learning (EdxArchive) 1 个评论 关注

开始时间: 04/22/2022 持续时间: 5 weeks

主页: https://www.edx.org/archive/scalable-machine-learning-uc-berkeleyx-cs190-1x

简介: Learn the underlying principles required to develop scalable machine learning pipelines and gain hands-on experience using Apache Spark.

Automata (CourseraArchive) 3 个评论 关注

开始时间: 04/22/2022 持续时间: 6 weeks

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

简介: This course covers finite automata, context-free grammars, Turing machines, undecidable problems, and intractable problems (NP-completeness).