Feature engineering is a crucial step in the machine-learning pipeline, yet this topic is rarely examined on its own. With this practical book, you’ll learn techniques for extracting and transforming features—the numeric representations of raw data—into formats for machine-learning models. Each chapter guides you through a single data problem, such as how to represent text or image data. Together, these examples illustrate the main principles of feature engineering.
Rather than simply teach these principles, authors Alice Zheng and Amanda Casari focus on practical application with exercises throughout the book. The closing chapter brings everything together by tackling a real-world, structured dataset with several feature-engineering techniques. Python packages including numpy, Pandas, Scikit-learn, and Matplotlib are used in code examples.
You’ll examine:

• Feature engineering for numeric data: filtering, binning, scaling, log transforms, and power transforms
• Natural text techniques: bag-of-words, n-grams, and phrase detection
• Frequency-based filtering and feature scaling for eliminating uninformative features
• Encoding techniques of categorical variables, including feature hashing and bin-counting
• Model-based feature engineering with principal component analysis
• The concept of model stacking, using k-means as a featurization technique
• Image feature extraction with manual and deep-learning techniques
  

掃碼或添加微信號：壇友素質(zhì)互助

「經(jīng)管之家」APP：經(jīng)管人學(xué)習(xí)、答疑、交友，就上經(jīng)管之家！
免流量費下載資料----在經(jīng)管之家app可以下載論壇上的所有資源，并且不額外收取下載高峰期的論壇幣。
涵蓋所有經(jīng)管領(lǐng)域的優(yōu)秀內(nèi)容----覆蓋經(jīng)濟、管理、金融投資、計量統(tǒng)計、數(shù)據(jù)分析、國貿(mào)、財會等專業(yè)的學(xué)習(xí)寶庫，各類資料應(yīng)有盡有。
來自五湖四海的經(jīng)管達人----已經(jīng)有上千萬的經(jīng)管人來到這里，你可以找到任何學(xué)科方向、有共同話題的朋友。
經(jīng)管之家（原人大經(jīng)濟論壇），跨越高校的圍墻，帶你走進經(jīng)管知識的新世界。
掃描下方二維碼下載并注冊APP