示例数据

🚀 机器学习代码示例精选 📚

📌 Python 实现线性回归

```python import numpy as np from sklearn.linear_model import LinearRegression

X = np.array([[1], [2], [3], [4], [5]]) y = np.array([2, 4, 6, 8, 10])

model = LinearRegression().fit(X, y) print("预测值:", model.predict([[6]]))

> 📚 [点击查看完整教程](/data-science-blog/machine_learning/introduction)

### 📌 R 语言决策树分类
<center><img src="https://cloud-image.ullrai.com/q/决策树/" alt="决策树"/></center>
```r
library(rpart)
data(iris)
tree_model <- rpart(Species ~ ., data = iris, method = "class")
print(tree_model)

📌 探索更多R语言实战案例

📌 Julia 语言神经网络训练

```julia using Flux

model = Chain(Dense(10, 5, relu), Dense(5, 2)) loss = Flux mse_loss(model, X, y)

> 🧠 [深入学习Julia机器学习框架](/data-science-blog/machine_learning/advanced_topics)

### 📚 推荐扩展阅读
- [机器学习基础概念图解](/data-science-blog/machine_learning/concepts)
- [深度学习框架对比指南](/data-science-blog/machine_learning/frameworks)
- [代码优化技巧合集](/data-science-blog/machine_learning/optimization)