machine-learning
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jackzhenguo
Python, data analysis, machine learning...
Road to AI
It is all about practical experience and best study materials for AI
- this repository is still updating...
Contribution
Great thanks to brother yun contributing to this repository! Welcome more to contribute!
basics
Basics model includes some essentially fundamental algorithms,such as bisection, Dijstra, common sort algorithms and so on.
math
Math model is exactly its seeming name, about math theories, especially about optimization, linear algebra, probabilty theory.
python
Python model is mainly for machine learning and deep learning ,such as decorator, generator, highOrder function, etc and that is to say, doesn't include everything knowledge about Python, currently including:
- 装饰器极简入门
- 生成器极简入门
- 高阶函数极简入门
- itertools之groupby
- 24式加速你的Python
- Python63个内置函数
- Type Checking
- 列表生成式
- Collections模块
- itertools模块
numpy
Numpy model is about numpy summaries in practice, currently including:
pandas
Pandas model is about pandas summaries in practice.
- Pandas实战总结1
- Pandas列索引获取方法
- Pandas列排序
- Pandas去重操作使用举例
- Pandas的loc索引
- Pandas的merge应用例子
- Pandas的多索引、轴、排序
- Pandas的Series使用例子
- Pandas的DataFrame使用例子
- to_csv乱码解决方法一
- Pandas处理缺失值实战
ml
ML model is mainly about ml skill stack, including feature engineering, pca, common ml algorithms, etc. Importantly, each step of machine learning is provided the reference materials which are picked up elaborately, currently including:
- 入门机器学习，这是我见过的最直白讲解
- 单词拼写检查器
- 决策树做回归和分类及可视化
- 主成分分析之 PCA, SVD
- 手写 高斯混合GMM算法
- 手写 线性回归实战
- 手写 逻辑回归实战
- xgboost基础入门
- 梯度提升树(GBDT)完整教程 V1.1 发布.pdf
- 最常用的降维算法tsne
dl
DL model,deep learning part contains theory about cv and nlp.
Best study materials for deep learning:
kaggle
Kaggle model is about in pracitce and contains sorts of practical experience.
tensorflow
Tensorflow model, tensorflow skeleton will be noted from introductory to practical application to projects.
jackzhenguo