Note for CS231N: CNN for Visual Recognition

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Review data structure & algorithm

  First: Cracking the coding interview 20/9 Chapter 1: The interview process - Analytical skills - Coding skills - Technical knowledge / Computer Science fundamentals - Experience - Culture fit / Communication skills Chapter 5: Behavioral questions - Go through each of the projects or components of your resume and ensure that you can talk about them in detail. Challenge -  Mistakes/Failures - Enjoyed - Leadership - Conflicts - What You'd do Differently Business problem - Analytics - How to implement Chapter 6: Big O Technique dynamic programming: memoization, tabulation. Chapter 7: Technical questions Listen -> Example -> Brute force -> Optimize (BUD: Bottlenecks, unnecessary work, duplicated work) -> Walk through -> Implement -> Test Listen: information -> input/output, optimal keyword. Brute force: space/time complexity and then dive into improvement. Optimize:   1. Look for any unused information. 2. Use a fresh example. 3. Make time/space tradeof...
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Review Machine Learning

First of all, I will review the theory of ML from machinelearningcoban.com to better understand the algorithm. It's important to give some examples and explain the business problem. Regression: 1. Linear regression 2. Logistic regression Classification: 1. Linear classification 2. SVM 3. Kernel SVM 4. Softmax Instance-based: 1. k-NN Clustering: 1. k-Means Artificial neural network: 1. Perceptron 2. Softmax regression 3. Multi-layer Perceptron 4. Back-Propagation Dimensionality: 1. PCA 2. LDA Ensemble: 1. Boosting 2. AdaBoost 3. Random forest Ở phần này mình cũng sẽ sử dụng tài liệu của mlcourse.ai để ôn tập. Một tài liệu nền tảng hơn nữa là khóa Learning from the data của đại học Caltech,   một phiển bản được diễn giải tốt hơn nữa là ở đây  https://www.csie.ntu.edu.tw/~htlin/talk/doc/mlbasic.bdml.handout.pdf 1. Linear regression 2. Logistic regression Logistic regression là trường hợp đặc biệt của linear classification. Model này add vào benefit of predicting a probability. V...
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