木加_子贝

北京 海淀区

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

开始时间: 04/22/2022 持续时间: 未知

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

简介: This course concentrates on recognizing and solving convex optimization problems that arise in applications. The syllabus includes: convex sets, functions, and optimization problems; basics of convex analysis; least-squares, linear and quadratic programs, semidefinite programming, minimax, extremal volume, and other problems; optimality conditions, duality theory, theorems of alternative, and applications; interior-point methods; applications to signal processing, statistics and machine learning, control and mechanical engineering, digital and analog circuit design, and finance.

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

开始时间: 04/22/2022 持续时间: 未知

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

简介: This is an introductory-level course in supervised learning, with a focus on regression and classification methods. The syllabus includes: linear and polynomial regression, logistic regression and linear discriminant analysis; cross-validation and the bootstrap, model selection and regularization methods (ridge and lasso); nonlinear models, splines and generalized additive models; tree-based methods, random forests and boosting; support-vector machines. Some unsupervised learning methods are discussed: principal components and clustering (k-means and hierarchical).

Recommender Systems Specialization (Coursera专项课程) 0 个评论 关注

开始时间: 12/21/2023 持续时间: Approximately 5 months to complete Suggested pace of 3 hours/week

主页: https://www.coursera.org/specializations/recommender-systems

简介: 明尼苏达大学的推荐系统专项课程系列(Recommender Systems Specialization),这个系列由4门子课程和1门毕业项目课程组成,包括推荐系统导论,最近邻协同过滤,推荐系统评价,矩阵分解和高级技术等,感兴趣的同学可以关注:Master Recommender Systems-Learn to design, build, and evaluate recommender systems for commerce and content.

Parallel, Concurrent, and Distributed Programming in Java Specialization (Coursera专项课程) 0 个评论 关注

开始时间: 12/21/2023 持续时间: Approximately 3 months to complete Suggested pace of 5 hours/week

主页: https://www.coursera.org/specializations/pcdp

简介: Java并行,并发和分布式编程专项课程系列(Parallel, Concurrent, and Distributed Programming in Java Specialization),这个系列包含3个子课程,分别是Java并行编程,Java并发编程和Java分布式编程,感兴趣的同学可以关注:Boost Your Programming Expertise with Parallelism-Learn the fundamentals of parallel, concurrent, and distributed programming.

Robotics Specialization (Coursera专项课程) 0 个评论 关注

开始时间: 12/21/2023 持续时间: Approximately 7 months to complete Suggested pace of 5 hours/week

主页: https://www.coursera.org/specializations/robotics

简介: 宾夕法尼亚大学的机器人专项课程系列(Robotics Specialization),这个系列包括5门子课程和1门毕业项目课程,涵盖空中机器人(微型飞行器),运动规划,可动性,感知能力,预测和学习等内容,感兴趣的同学可以关注:Learn the Building Blocks for a Career in Robotics-Gain experience programming robots to perform in situations and for use in crisis management

Deep Learning Specialization (Coursera专项课程) 0 个评论 关注

开始时间: 12/21/2023 持续时间: Approximately 5 months to complete Suggested pace of 9 hours/week

主页: https://www.coursera.org/specializations/deep-learning

简介: Andrew Ng老师的深度学习专项系列课程(Deep Learning Specialization) ,入门深度学习首选课程。这个系列包含5门子课程,涵盖神经网络与深度学习,调参优化,机器学习项目架构,卷积神经网络和递归神经网络,感兴趣的同学可以关注:Deep Learning Specialization-Master Deep Learning, and Break into AI

Applied Machine Learning in Python (CourseraArchive) 0 个评论 关注

开始时间: 04/22/2022 持续时间: Unknown

主页: https://www.coursera.org/archive/python-machine-learning

简介: Python应用课程,这门课程主要聚焦在通过Python应用机器学习,包括机器学习和统计学的区别,机器学习工具包scikit-learn的介绍,有监督学习和无监督学习,数据泛化问题(例如交叉验证和过拟合)等。

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