文件名称：机器学习：带有机器学习示例的笔记本
文件大小：11.42MB
文件格式：ZIP
更新时间：2024-02-26 17:37:09
machine-learning tensorflow numpy scikit-learn matplotlib
机器学习 带有机器学习示例的笔记本 Scikit学习Keras Tensorflow Spark ML
【文件预览】：
machine-learning-master
----Appendix A - Activation Functions.ipynb(97KB)
----Scikit - 17 Classification non linear decision boundary.ipynb(329KB)
----Scikit - 10 Image Classification (MNIST dataset).ipynb(338KB)
----Scikit - 28 Clustering - Online Retail Sales Data.ipynb(79KB)
----SparkML - 01 Regression.ipynb(33KB)
----Scikit - 04 Linear Regression - Kaggle Housing.ipynb(53KB)
----Scikit - 03 Linear Regression.ipynb(752KB)
----demos()
--------Day 2 - Regression Demo.ipynb(98KB)
--------Day 1 - note pandas, np, matplotlib.ipynb(374KB)
--------Day 1 - Pandas, Numpy and Matplotlib.ipynb(26.26MB)
--------Day 4 - cnn - mnist.ipynb(136KB)
--------Day 3 - nn - mnist.ipynb(126KB)
----Flask-ML()
--------app.py(966B)
--------rest-app.py(2KB)
--------templates()
--------train.py(2KB)
--------.idea()
--------requirements.txt(47B)
--------readme.txt(1KB)
----Spacy.ipynb(33KB)
----Scikit - 19 Markov Chain.ipynb(3KB)
----SparkML - 06 Movie Recommendation.ipynb(187KB)
----Scikit - 08 Clustering.ipynb(349KB)
----Scikit - 16 Time Series - PerCapitaGDP.ipynb(314KB)
----SparkML - 04 Text_Analysis.ipynb(50KB)
----Scikit - 20 Kaggle House Data Preprocessing.ipynb(415KB)
----Scikit - 25 tSNE Clustering (MNIST dataset).ipynb(349KB)
----Scikit - 29 Build End to End pipeline.ipynb(34KB)
----Scikit - 31 Credit Card Fraud Classification Problem.ipynb(27KB)
----SparkML - 02 Credit Default.ipynb(56KB)
----Pandas DataFrame.ipynb(27KB)
----Scikit - 09 Clustering on Medical Image.ipynb(210KB)
----Pandas Profile Report.ipynb(1.68MB)
----Time Series - Stock Price Forecast using ARIMA.ipynb(468KB)
----Scikit - 06 Text Processing.ipynb(236KB)
----LICENSE(11KB)
----opencv()
--------Basic Image Processing.ipynb(4.4MB)
----Scikit - 12 Neural Network using Numpy.ipynb(340KB)
----Scikit - 02 Visualization.ipynb(289KB)
----SparkML - 07 Click Prediction (Outbrain dataset).ipynb(281KB)
----Scikit - 23 PCA (kdd cup 1999).ipynb(35KB)
----Scikit - 24 Text Analytics - StumbleUpon Evergreen.ipynb(49KB)
----SparkML - 03 Image Classification (MNIST).ipynb(85KB)
----Appendix B - Working with database.ipynb(21KB)
----Scikit - 22 Regression - Istanbul Stock Market.ipynb(540KB)
----Linear Algebra.ipynb(15KB)
----Scikit - 01 Data Preprocessing.ipynb(123KB)
----SparkML - 05 Credit card Fraud.ipynb(24KB)
----yoochoose- Retail Prediction. 2015.ipynb(85KB)
----compare.py(1KB)
----Scikit - 18 KDD 1999 (Anamoly detection).ipynb(122KB)
----.gitignore(113B)
----RL()
--------RL.iml(338B)
--------frozen-lake.py(355B)
--------mountain-car.py(407B)
--------requirements.txt(15B)
--------frozenlake8x8_valueiteration.py(2KB)
----Bird Tracking (EDA).ipynb(294KB)
----Scikit - 15 Learning Curve and Tuning .ipynb(193KB)
----Scikit - 30 Ensemble, Bagging, Pasting, Boosting.ipynb(40KB)
----Scikit - 05 Classification.ipynb(349KB)
----Text2Speech()
--------app.py(805B)
--------bin()
--------templates()
--------awsclient.py(4KB)
--------static()
--------requirements.txt(51B)
--------readme.txt(1KB)
----README.md(100B)
----Telecomm Churn Analysis Using XGBoost.ipynb(470KB)
----COVID-19.ipynb(1.54MB)
----Scikit - 27 Sklearn Pipeline.ipynb(48KB)
----Scikit - 26 Clustering SNS Data.ipynb(87KB)
----Utils.py(7KB)
----Scikit - 21 Kaggle House price prediction (regression).ipynb(293KB)
----Bank - Marketing Campaign.ipynb(28KB)
----Scikit - 07 Dimensionality Reduction.ipynb(163KB)