Selected Computer Vision Tutorials
Computer Vision is a diverse research domain encompassing various topics. This guide compiles essential and up-to-date tutorials, carefully selected from those presented at top-tier conferences in the field, including CVPR, ICCV, ECCV, and SIGGRAPH.
ProbML
Context: Welcome to the reading guide for “Probabilistic Machine Learning” by Kevin Murphy. The first version of this book, published in 2012 (probml.github.io/pml-book/book0.html) gained widespread recognition in the Machine Learning community and was often referred to as the “Bible of Machine Learning.” The book’s popularity stemmed from its comprehensive coverage of a vast array of Machine Learning topics, providing readers with a deep understanding of the subject. Recognizing the rapidly evolving landscape of Machine Learning, Kevin Murphy has taken the initiative to update and expand the knowledge presented in the original book. As a result, he decided to release a new version of the book, dividing it into two separate volumes with a total of more than 2000 pages. The first book serves as a core introduction to the subject, while the second book delves into more advanced topics.
PhD Guidance
This is the PhD guidance from my own experience including:
- (1) Defining your goals
- (2) How to choose a university and a professor
- (3) The needed mindset
- (4) The worth noting things in research
- (5) Career paths after graduation
- (6) Attitude after graduation
It is specially written for Vietnamese student, but you can use Google Translate for your convinence.
Overview of Machine Learning
This is my first post on Machine Learning, Deep Learning and Computer Vision series in Medium. I am currently a Ph.D. Student in Computer Science with research interests are Computer Vision and Machine Learning. On this series, I will share with you the roadmap I have experienced. I hope that everything I share is somehow helps you save time when exploring Machine Learning field.
How to use Google Scholar for advancing your research
One of the most powerful and common tools for your research is Google Scholar. It contains many useful features that are necessary for your research. If you can make use of it, you do not need any proprietary software. In this article, I will introduce some useful features namely Google Scholar Search, My Profile, My library, Alerts, and Metrics.
Introduction to Machine Learning
This is the overview of basic and important machine learning models, methods and concepts and theories. I acknowledge all information and knowledge including images, data… I have taken from those two courses: https://www.coursera.org/learn/machine-learning and http://classes.engr.oregonstate.edu/eecs/fall2015/cs534/.