数学在机器学习领域的应用. Learn about the prerequisite mathematics for applications in data science and machine learning
Through the assignments of this specialisation you will use the skills you have learned to produce mini-projects with Python on interactive notebooks, an easy to learn tool which will help you apply the knowledge to real world problems. For example, using linear algebra in order to calculate the page rank of a small simulated internet, applying multivariate calculus in order to train your own neural network, performing a non-linear least squares regression to fit a model to a data set, and using principal component analysis to determine the features of the MNIST digits data set.
Taught in an intuitive way. Never have I been able to understand linear algebra better than after following the first 3 weeks of this course. I can't wait to complete the entire specialization
Overall the hardest of the specialization, a though one but great to make sense of all the maths learned so far.
Another great course from Imperial College London. I highly recommend this specialization.
I have thoroughly enjoyed every course of this specialization. Thank you very much.
It was a good course compared to other two courses of this specialization.
Very Well Explained. Good content and great explanation of content. Complex topics are also covered in very easy way. Very Helpful for learning much more complex topics for Machine Learning in future.
Excellent review of Linear Algebra even for those who have taken it at school. Handwriting of the first instructor wasn't always legible, but wasn't too bad. Second instructor's handwriting is better.
Excellent course. I completed this course with no prior knowledge of multivariate calculus and was successful nonetheless. It was challenging and extremely interesting, informative, and well designed.
此课程是 100% 在线学习吗？是否需要现场参加课程？
3/4 hours a week for 3 to 4 months
What background knowledge is necessary?
High school maths knowledge is required. Basic knowledge of Python can come in handy, but it is not necessary for courses 1 and 2. For course 3 (intermediate difficulty) you will need basic Python and numpy knowledge to get through the assignments.
Do I need to take the courses in a specific order?
We recommend taking the courses in the order in which they are displayed on the main page of the Specialization.
This is a non-credit Specialization.
What will I be able to do upon completing the Specialization?
At the end of this Specialization you will have gained the prerequisite mathematical knowledge to continue your journey and take more advanced courses in machine learning.