搜索资源列表
AdaBoost
- 用python实现的AdaBoost分类算法，文件是一个ipython notebook，可以直接用ipython/jupyter打开使用。内附简单测试数据集。 程序运行需要numpy库的支持。-An AdaBoost classifier implemented with Python.
deeplearningbook-chinese-master
- Python机器学习代码示例，包含了全部的书本的代码示例，可以通过jupyter notebook直接运行文件显示结果(Python Machine Learning)
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- yongyudakaixuexikuangjibkjaldbndkjbasn,das(jupyter notebook gkahbk dbaiuhdkj haskljnkajf fasf sd)
House Price Regression
- 经典的房价预测问题，用jupyter notebook编写的简单实现。使用XGBoost模块进行学习预测。(The classic price prediction problem, a simple implementation written in jupyter notebook. The XGBoost module is used for learning prediction.)
deep-learning-with-python-notebooks-master
- Deep Learning With Python 原书配套代码。 包括所有常见的深度学习模型 注释丰富，代码规范 使用流行的keras库实现，jupyter notebook格式(Deep Learning With Python Original book matching code. Including all the common deep learning models Rich annotation, code specification Using the popula
PyData-D3-in-Jupyter
- 在jupyter notebook中嵌入D3.js可视化(Embedding D3.js visualization in jupyter notebook)
subway_prediction_notebook
- jupyter notebook of subway prediction kaggle
最小二乘法-梯度下降法-牛顿法
- 用Python3在jupyter notebook实现最小二乘法，梯度下降法和牛顿法(Using Python3 to realize least square method, gradient descent method and Newton method in jupyter notebook)
天池比赛源码
- 天池比赛 商铺定位的数据处理源码，通过jupyter notebook使用
fault_synth_batch
- 合成地震断层数据，python程序语言，可以直接在jupyter notebook运行(Synthetic seismic tomographic data, python programming language, can be run directly on jupyter notebook)
1_Neural Network & DeepLearning
- 吴恩达深度学习微专业课程一配套作业，jupyter notebook格式的(Wu enda deep learning micro professional course a matching homework)
梯度下降法 回溯直线搜索 python代码
- 梯度下降法 回溯直线搜索 python代码 包含回溯直线搜索，以及初始值相同时不同alpha,beta值对下降速度的影响测试 用jupyter notebook打开
LSTM-单变量多步
- 用jupyter notebook 实现深度学习LSTM单变量多步的时间序列预测(Using jupyter notebook to realize multi-step time series prediction of deep learning LSTM)
python机器学习
- python机器学习Chapter1.4的示例代码。使用jupyter notebook。python2.
Dive into DL Pytorch 源代码
- Dive into DL Pytorch源代码，jupyter notebook