課程目標

• 介紹關於Python於大數據資料處理演算法之架構、流程與實作。並介紹深度學習演算法

用書

Learning Data Mining with Python, Robert Layton, Packt, 2015

• 1. Getting Started with Data Mining
• 2. Classifying with scikit-learn Estimators
• 3. Predicting Sports Winners with Decision Trees
• 4. Recommending Movies Using Affinity Analysis
• 5. Extracting Features with Transformers
• 6. Social Media Insight Using Naïve Bayes
• 7. Discovering Accounts to Follow Using Graph Mining Loading the dataset
• 8. Beating CAPTCHAs with Neural Networks
• 9. Authorship Attribution
• 10. Clustering News Articles
• 11. Classifying Objects in Images Using Deep Learning
• 12. Working with Big Data

Machine Learning in Python, Michael Bowles, Wiley, 2015

• 1. The Two Essential Algorithms for Making Predictions
• 2. Understand the Problem by Understanding the Data
• 3. Predictive Model Building: Balancing Performance, Complexity, and Big Data
• 4. Penalized Linear Regression
• 5. Ensemble Methods
• 6. Building Ensemble Models with Python