UCSD《离散数学(数学思维、组合和概率论、图论、数论和密码学、送货问题)|Discrete Mathematics》中英字幕 1891 -- 32:06:19 App CMU Discrete Mathematics 4.1万 253 33:12:14 App 【MIT6.042J中英文字幕】离散数学 Mathematics for Computer Science, Fall 2010 6272 2 1:09:53 App 【离散数学及其应用】【...
This course covers elementary discrete mathematics for computer science and engineering. It emphasizes mathematical definitions and proofs as well as applicable methods. Topics include formal logic notation, proof methods; induction, well-ordering; sets, relations; elementary graph theory; integer congruence...
If you're interested in an accessible introduction to matrix algebra, Coursera is running a course on it right now: Coding the Matrix: Linear Algebra through Computer Science ApplicationsThe applied math most directly useful for machine learning is: Statistics (See How do I learn statistics for ...
Second course in Coursera Mathematics for Machine Learning specialization. The Matrix Calculus You Need For Deep Learning paper. MIT Single Variable Calculus. MIT Multivariable Calculus. Stanford CS224n Differential Calculus review. Statistics and Probability Used in data science to analyze and visualize ...
MathematicsIsAScience- Peter Saveliev (Professor of mathematics at Marshall University, Huntington WV, USA) Meetings and Conferences MathsJam- monthly local recreational maths/puzzle meetups and an annual gathering in Staffordshire, England Talking Maths in Public- a conference for maths communicators, ru...
Stochastic processes Numerical Analysis Signal processing Mathematics for Computer Science Mathematical Biology Mathematical Physics Students Lecture Notes Related Awesome Lists LicenseAwesome Math A curated list of awesome mathematics resources.All resources are freely available except those with a 💲 icon.Con...
Code Issues Pull requests [Coursera] Introduction to Discrete Mathematics for Computer Science Specialization cryptography probability coursera discrete-mathematics graph-theory combinatorics number-theory coursera-discrete-mathematics Updated Sep 5, 2021 Jupyter Notebook rafi...
There is a path here for the skilled technician to create tools, plug-in’s and even operational systems that use machine learning. The technician is contrasted to the theoretician at the other end of the scale. The theoretician can: ...
Apart from academia, Dipanjan is a big fan of MOOCs. He also beta-test new courses for Coursera before they are made public. Dipanjan is also a Google Developer Expert in Machine Learning and has worked with several Fortune 500 companies. For an expert in ML, mathematics is a prerequisite,...
January 16, 2019 in Academic, Computer Science, Machine Learning, Mathematics, Probability, Statistics, Useful for referring | Leave a comment A nice blog on CS including learnings: https://blog.acolyer.org/ called “the morning paper”: an interesting/influential/important paper from the world...