Setup your beautiful and powerful terminal with ZSH + Oh My Zsh + Powerlevel10k
03 October 2021
The final results of this setup.
read moreMachine Learning Note: Support Vector Machine (2)
06 March 2020
4. Kernel SVM 4.1 Kernel Trick Recall the dual form of the SVM problem:
read moreMachine Learning Note: Support Vector Machine (1)
18 November 2019
1. Intuition of SVM Assume that we have some data points of two different classes which are linear separable. In the case of two dimensional data, we can use a line $y = w^Tx + b$ to separate it. If the data are high dimensional, we can use a hyperplane to separate it.
read moreMachine Learning Note: Duality
17 November 2019
1. Lower bound property Given an optimization problem with the following standard form:
read morePaper Summary: From Word Embeddings To Document Distances
13 November 2019
Paper Title: From Word Embeddings To Document Distances
read moreSolving a simple transportation problem using CVXOPT
12 November 2019
Problem Description Assume that we are the manager of a support chain. Our company has two factory A and B, and each of them has 300 and 250 products, respectively. Now we would like to deliver them two three retail stores in different cities 1, 2, 3. There is a cost for each delivery as listed below.
read moreMachine Learning Note - Convex Optimization
11 November 2019
Introduction I’ve been taking an online Machine Learning class recently. This post is my note on convex optimization part.
read moreTraining A Self-Driving Car to Learn from Human Driving Behavior
09 August 2018
I was enrolled in the Udacity Self-Driving Nanodegree starting from this summer, and this is my solution to the behavior cloning project in my Nanodegree courses. Comparing to other solution that could be found on the web, this solution is clean and simple, and the resulting model can drive the car perfectly on both tracks. The code and trained model of this project are available on [Github].
read moreSet Up A New Deep Learning Server
15 June 2018
Updates: I found that CUDA and cuDNN can be installed through Anaconda, and it has a lot of benifits (e.g install different versions of CUDA and cuDNN in different environment). So I ended up switching to this method and we don’t need to install them globally anymore.
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