Machine Learning & Computational Statistics Course
Course Intro: This course covers a wide variety of topics in machine learning and statistical modeling. While mathematical methods and theoretical aspects will be covered, the primary goal is to provide students with the tools and principles needed to solve the data science problems found in practice.
https://davidrosenberg.github.io/ml2016/#home
#machine_learning #statistics #course
Course Intro: This course covers a wide variety of topics in machine learning and statistical modeling. While mathematical methods and theoretical aspects will be covered, the primary goal is to provide students with the tools and principles needed to solve the data science problems found in practice.
https://davidrosenberg.github.io/ml2016/#home
#machine_learning #statistics #course
New Deep Learning Course by Yann LeCun & Alfredo Canziani (Recommended)
Course Intro: This course concerns the latest techniques in deep learning and representation learning, focusing on supervised and unsupervised deep learning, embedding methods, metric learning, convolutional and recurrent nets, with applications to computer vision, natural language understanding, and speech recognition.
Additional Info: This course is available in 11 languages such as Persian, and I personally translated some of the materials of this course to Persian :).
https://atcold.github.io/pytorch-Deep-Learning/
#deep_learning #course
Course Intro: This course concerns the latest techniques in deep learning and representation learning, focusing on supervised and unsupervised deep learning, embedding methods, metric learning, convolutional and recurrent nets, with applications to computer vision, natural language understanding, and speech recognition.
Additional Info: This course is available in 11 languages such as Persian, and I personally translated some of the materials of this course to Persian :).
https://atcold.github.io/pytorch-Deep-Learning/
#deep_learning #course