Python Machine Learning

Description

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