
AshishSingh Bhatia Bostjan Kaluza
As the amount of data in the world continues to grow at an almost incomprehensible rate, being able to understand and process data is becoming a key differentiator for competitive organizations. Machine learning applications are everywhere, from self-driving cars, spam detection, document search, and trading strategies, to speech recognition. This makes machine learning well-suited to the present-day era of big data and Data Science. The main challenge is how to transform data into actionable knowledge.Machine Learning in Java will provide you with the techniques and tools you need. You will start by learning how to apply machine learning methods to a variety of common tasks including classification, prediction, forecasting, market basket analysis, and clustering. The code in this book works for JDK 8 and above, the code is tested on JDK 11.Moving on, you will discover how to detect anomalies and fraud, and ways to perform activity recognition, image recognition, and text analysis. By the end of the book, you will have explored related web resources and technologies that will help you take your learning to the next level.By applying the most effective machine learning methods to real-world problems, you will gain hands-on experience that will transform the way you think about data.
本書主要分成了以下幾個部分: 1. 理論概念的表達 2. 重要依賴庫的分析和比較 3. 機器學習的三大主要流程:分類,迴歸和聚類 4. 機器學習在不同領域的典型應用 要理論有理論,要代碼有代碼,如果建立版本控制堅持閱讀並完全消化,可以理解很多生活中實際問題的解決方案。