Search result for Randomized algorithms Online Courses & Certifications
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Introduction to Graduate Algorithms
by Eric Vigoda , Arpan Chakraborty- 0.0
Approx. 3 months
The design and analysis of algorithms form an essential basis for computer science. Learn advanced techniques for designing algorithms and apply them to hard computational problems....
Free
Algorithms for Searching, Sorting, and Indexing
by Sriram Sankaranarayanan- 4.6
Approx. 34 hours to complete
This course covers basics of algorithm design and analysis, as well as algorithms for sorting arrays, data structures such as priority queues, hash functions, and applications such as Bloom filters. Algorithms for Searching, Sorting, and Indexing can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform....
Algorithms, Part I
by Kevin Wayne , Robert Sedgewick- 4.9
Approx. 54 hours to complete
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. Analysis of Algorithms Analysis of Algorithms Introduction Theory of Algorithms...
Build Regression, Classification, and Clustering Models
by Anastas Stoyanovsky- 0.0
Approx. 20 hours to complete
Models are constructed using algorithms, and in the world of machine learning, there are many different algorithms to choose from. Ultimately, this course begins a technical exploration of the various machine learning algorithms and how they can be used to build problem-solving models. Randomized Search Genetic Algorithms...
機器學習技法 (Machine Learning Techniques)
by 林軒田- 0.0
Approx. 19 hours to complete
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。] 第一講:Linear Support Vector Machine Course Introduction Large-Margin Separating Hyperplane Standard Large-Margin Problem Support Vector Machine Reasons behind Large-Margin Hyperplane NTU MOOC 課程問題詢問與回報機制...