一文看懂自然语言处理NLP(4个应用+5个难点+6个实现步骤)
Attention 机制
Encoder-Decoder 和 Seq2Seq
Q-Learning
Adaboost 算法
随机森林 - Random forest
学习向量量化 - Learning vector quantization | LVQ
K邻近 - k-nearest neighbors | KNN
线性判别分析 - Linear Discriminant Analysis | LDA
TF-IDF
元学习 - Meta learning
遗传算法(Genetic algorithm | GA)
判别式模型(Discriminative model)
产生式模型(Generative model)
Latent Dirichlet Allocation|LDA
启发式算法 - Heuristic
粒子群算法(Particle swarm optimization | PSO)
人工神经网络 - Artificial Neural Network | ANN
迁移学习(Transfer learning)
长短期记忆网络 - Long short-term memory | LSTM
生成对抗网络 - Generative Adversarial Networks | GAN
循环神经网络 - Recurrent Neural Network | RNN
卷积神经网络 - CNN
受限玻尔兹曼机(Restricted Boltzmann machine | RBM)
强化学习-Reinforcement learning | RL
自编码器(Autoencoder)
前馈神经网络(Feedforward neural network)
模糊神经网络(Neuro-fuzzy | FNN)
自组织映射(Self-organization map | SOM)
K均值聚类(k-means clustering)
反向传播算法(Backpropagation)
集成学习(Ensemble Learning)
支持向量机 - Support Vector Machine | SVM
决策树 - Decision tree
逻辑回归 - Logistic regression
朴素贝叶斯 - Naive Bayes classifier | NBC
线性回归 - linear regression
机器学习 - machine learning | ML