Python Machine Learning

Brief Contents......Page 3
Contents......Page 4
Introduction......Page 10
Intro to Machine Learning......Page 12
What Is Machine Learning?......Page 13
Getting the Tools......Page 19
Summary......Page 29
What Is NumPy?......Page 30
Creating NumPy Arrays......Page 31
Array Indexing......Page 33
Reshaping Arrays......Page 37
Array Math......Page 38
Array Assignment......Page 45
Summary......Page 49
Manipulating Tabular Data using Pandas......Page 50
Pandas Series......Page 51
Pandas DataFrame......Page 56
Summary......Page 75
Data Visualization using matplotlib......Page 77
Plotting Line Charts......Page 78
Plotting Bar Charts......Page 83
Plotting Pie Charts......Page 87
Plotting Scatter Plots......Page 93
Plotting Using Seaborn......Page 95
Summary......Page 101
Start with Scikit-learn for ML......Page 102
Getting Datasets......Page 103
Getting Started with Scikit-learn......Page 109
Data Cleansing......Page 116
Summary......Page 126
Supervised Learning - Linear Regression......Page 127
Linear Regression......Page 128
Polynomial Regression......Page 143
Summary......Page 157
Supervised Learning - Classification using Logistic Regression......Page 158
Using the Breast Cancer Wisconsin (Diagnostic) Data Set......Page 163
Summary......Page 182
Supervised Learning - Classification using SVMs......Page 183
Kernel Trick......Page 192
Types of Kernels......Page 197
Using SVM for Real-Life Problems......Page 206
Summary......Page 209
Supervised Learning - Classification using K-Nearest Neighbors (KNN)......Page 210
Summary......Page 225
Unsupervised Learning - Clustering using K-Means......Page 226
Using K-Means to Solve Real-Life Problems......Page 241
Summary......Page 247
Azure Machine Learning Studio......Page 248
Summary......Page 271
Deploying Machine Learning Models......Page 273
Case Study......Page 274
Deploying the Model......Page 284
Creating the Client Application to Use the Model......Page 287
Summary......Page 288
Index......Page 289