往期文章集合目录

机器学习核心点整理

• Logistic Regression, L1, L2 regularization, Gradient/Coordinate descent 详细
• MLE v.s. MAP ~ L1, L2 Math Derivation 详细
• XGBoost math Derivation 通俗易懂的详细推导
• Introduction to Convex Optimization Basic Concepts 详细
• Convex Optimization: Primal Problem to Dual problem clearly explained 详细
• SVM/ Dual SVM math derivation, non-linear SVM, kernel function详细
• EM (Expectation–Maximization) Algorithm 思路分析及推导
• GMM & K-means 高斯混合模型和K-means聚类详解
• Intro to Deep Learning & Backpropagation 深度学习模型介绍及反向传播算法推导详解
• Knowledge Distillation 知识蒸馏详解

NLP 核心知识整理

• NLP基础概览 + Spell Correction with Noisy Channel
• Distributed representation, Hyperbolic Space, Gaussian/ Graph Embedding 详细介绍
• Skip-gram 详细推导加分析
• Hidden Markov Model (HMM) 详细推导及思路分析
• Probabilistic Graphical Model (PGM) 概率图模型框架详解
• Log-Linear Model & CRF 条件随机场详解
• RNN, LSTM 图文详解
• 常见多语言模型详解 (M-Bert, LASER, MultiFiT, XLM)

比赛经验分享

• Kaggle: Google Quest Q&A Labeling 首战银牌方法总结+心得
• Kaggle: Tweet Sentiment Extraction 方法总结 Part 1/2: 常用方法总结
• Kaggle: Tweet Sentiment Extraction 方法总结 Part 2/2: 金牌思路总结