[visionlist] Course on Machine Learning

Rizwan Ahmed Khan rizwan17 at gmail.com
Wed Feb 23 12:19:44 -05 2022

Dear Machine Learning / Data Science Enthusiasts,

It is my pleasure to apprise that I have made my course content related to
the course on "*Machine Learning*"* freely available for academic purposes*.

*Course Page:*


*Course Objectives:*

The *objective of this course* (16 weeks) is to introduce beginner to
intermediate level concepts of machine learning. Initially in this course,
the basic notion of data pre-processing is discussed as this step is
absolutely necessary before applying any machine learning algorithm to
extract patterns from the data. Most of this course will focus on
supervised machine learning algorithms and will train students so that they
can understand pros and cons of different algorithms and can select the
best algorithm for a given dataset / problem. To understand different
concepts discussed in this course, students are expected to have strong
familiarity with concepts of linear algebra, probability theory, analytical
geometry and multivariate calculus.


1.  Basic Intuition
2.  Supervised ML Problem Setup and Data Preprocessing
3.  Model Evaluation
4.  Lazy Lerners : kNN classifier
5.  Curse of Dimensionality
6.  Perceptron - Linear classifier
7.  Kernel Methods: SVM
8.  Explainable Models: Decision tree
9.  Linear Regression
10. Model Debugging and Ensemble Learning methods
11. Unsupervised Learning : K-Means Clustering
12. Biologically Inspired Models
    a. Logistic Regression
    b. Cross- Entropy Loss Function
    c. Gradient descent optimization algorithm
    d. Deep Neural Networks
    e. Application of chain rule for back propagation algorithm

*Associated Resources (Video Playlist)*:


Thank you.

#deeplearning #datascience #machinelearning #artificialintelligence #ai
#dataset #algorithms #python

Best Regards,
Rizwan Ahmed KHAN, PhD
Professor, Salim Habib (formerly Barrett Hodgson) University, Karachi,
preserve the color of our world – Think before you print.*
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://visionscience.com/pipermail/visionlist_visionscience.com/attachments/20220223/80038621/attachment.html>

More information about the visionlist mailing list