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UCSanDiegoX: DSE220x : Machine Learning Fundamentals Course

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# UCSanDiegoX: DSE220x : Machine Learning Fundamentals

### Course Instructor: Sanjoy Dasgupta, Professor of Computer Science and Engineering, UC San Diego

## Learning Objectives
This course is an intensive introduction to the most widely-used machine learning methods. 
* The first goal is to provide a basic intuitive understanding of these techniques: what they are good for, how they work, how they relate to one another, and their strengths and weaknesses. 
* The second goal is to provide a hands-on feel for these methods through experiments with suitable data sets, using Jupyter notebooks. 
* The third goal is to understand machine learning methods at a deeper level by delving into their mathematical underpinnings. This is crucial to being able to adapt and modify existing methods and to creatively combining them.

## Topics Covered
* Taxonomy of prediction problems
* Basics of Linear Algebra and Probability
* Nearest neighbor methods and families of distance functions
* Generalization: what it means; overfitting; selecting parameters using cross-validation
* Generative modeling for classification, especially using the multivariate Gaussian
* Linear regression and its variants
* Logistic regression
* Optimization: deriving stochastic gradient descent algorithms and testing convexity
* Linear classification using the support vector machine
* Nonlinear modeling using basis expansion and kernel methods
* Decision trees, boosting, and random forests
* Methods for flat and hierarchical clustering
* Principal component analysis
* Autoencoders, distributed representations, and deep learning

## Opinion/Comments
#### I audited for this course and pledged to complete it. I finished every Engagement, Quiz, Problem Set and Programming Assignment. I believe this is one of the best online course on fundamentals of ML as it maintains a right balance between theory and programming.

#### I have provided my Assignments here (as an evidence of finishing and maintaining a repository for the course), which I completed during a month's time with whatever knowledge I gathered during the course without any help. They are definitely not the efficient ones but correct for sure. Iff you fork it, found an efficient solution, don't forget to send a pull request.

#### Thanks for passing by!

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