applied-python-machine-learning
Applied Python Machine Learning Book
Chapter 2: Data Integration and Spark SQL
- Spark SQL
Chapter 3: Data Preparation
- Handle Missing Data
- Feature Selection
- Dimensionality Reduction
- Feature Scaling -Transforming Labels, Categorical and String Ordinal Data
- Data Partitioning
Chapter 4: Supervised learning for Business Applications
- Multiple Regression Analysis for House Price Prediction
- Multiclass Classification to Identify Glass Type
- Long Short-Term Memory (LTSM) Recurrent Neural in Time Series: Stock Exchange prediction
Chapter 5: Neural Networks
- Scikit-learn Neural Network for Face Completion
- Scikit-learn Neural Net for Multiclass Classification of Flowers
- Keras LSTM Recurrent Neural Net for Electrocardiogram (ECG) Anomaly Detection
Chapter 6: Medical Image Processing Applications by Scikit-image
- Scikit-image io Module to read, write and visualize images in various formats
- Scikit-image restoration Module to remove Medical Imaging noise
- Scikit-image color Module to separate colors of Immunohistochemical staining by color deconvolution method
- Scikit-image feature Module for X-Ray image segmentation
- Scikit-image exposure Module for Histogram equalization and X-ray image enhancement
Chapter 7: Unsupervised learning: scikit-learn’s PCA Business Applications
- Exploratory Analysis of Multi-Dimensional Dataset with Principle Component Analysis
- Dimensionally Reduction and Exploratory Analysis of the Faces Dataset with Principle Component Analysis
Chapter 8: Spark Machine Learning Library
- Spark’s Pipeline for Modeling, Evaluation and Tuning Parameters
- Spark MLlib's Multi Variable Linear Regression
- Spark MLlib's DecisionTree Regression
- Spark MLlib's RandomForest Regression
- Spark MLlib's DecisionTree for Multiclass Classification
- Spark MLlib's RandomForest for Multiclass Classification
- Spark MLlib's Multilayer Neural Net for Multiclass Classification
- Spark MLlib's Dimensionality Reduction by Principal Component Analysis
- MLlib's Collaborative Filtering Recommender Systems by Alternating Least Squares(ALS)
Chapter 9: Deep learning with TensorFlow: Image processing with Convolutional Neural Networks
- TensorFlow brief introduction
- Convolutional Neural Network for Multi class Image Classification
- Image classification by Inception-v3 trained model
- Retrain Inception's Final Layer for to classify Benign and Malignant Melanoma
Chapter 10: Deep learning with TensorFlow: Natural Language Processing
- Word2Vec for Vector Representations of Words
- Sentiment Analysis by LSTM Recurrent Neural Network (RNN)
- Syntactic parsing by Syntaxnet