NJU_AI 部分重要核心课程学习（with code）

1. 本学期课程：

NLP: Natural Language Processing (NJU)

PR&CV: Pattern Recognition and Computer Vision (NJU)

2. HKU Exchange:

NLP_COMP3361: Natural Language Processing (HKU exchange)

PR&ML_ELEC3249: Pattern Recognition and Machine Intelligence (HKU Exchange)

DA & M__EASC2410: Data_analysis_and_modeling (HKU Exchange)

3. 前序课程：

DS&A：数据结构与算法 (C++)

ICS：计算机系统基础 (C)

IntroAI：人工智能导论 (Java)

KRP：知识表示与处理 (Java)

ML：机器学习导论 (Python)

OS：操作系统 (C)

AML：advanced machine learning

1. homework1：multi-classification LR、 SVM、 EM、 low-rank PCA、 Metric Learning
2. homework2：sparse learning、 Graph Semi-supervised Learning、TSVM (python)
3. homework3: Gaussian Mixture Module, EM approach, Variational Inference, Reinforcement Rearning
4. homework4：Computational learning theory, $\beta-$uniform stablity(Ridge Regression), Covering number & Hoeffding, Model based Reinforcement Rearning(MDP)

DL：deep learning

1. homework1：CNN、VAE (pytorch)
2. homework2：implement AE、VAE、CVAE(version1: fully connected NN, version2: CNN) (pytorch)
3. homework3: whole galance(common problem in DL)
4. final article: Natural Language Processing, based on open information extraction(OIE)

数据库系统概论

DP：distributed parallel computing

1. project: parallel algorithms of QuickSort,EnumerateSort, MergeSort (Java)