Harness the power of Python to analyze data and create insightful predictive models About This Book * Learn data mining in practical terms, using a wide variety of Python libraries and techniques. * Learn how to find, manipulate, analyze and visualize data using Python. * Step-by-step instructions on creating real-world applications of data mining techniques with Python Who This Book Is For If you are a Python programmer who wants to get started with data mining, then this book is for you. If you are a data analyst who wants to leverage the power of Python to perform data mining efficiently, this book will also help you. No previous experience with data mining is expected. What You Will Learn * Apply data mining concepts to real-world problems * Predict the outcome of sports matches based on past results * Determine the author of a document based on their writing style * Use APIs to download datasets from social media and other online services * Find and extract good features from difficult datasets * Create models that solve real-world problems * Design and develop data mining applications using a variety of datasets * Perform object detection in images using Deep Neural Networks * Find meaningful insights from your data through intuitive visualizations * Compute on big data, including real-time data from the internet In Detail The next step in the information age is to gain insights from the deluge of data coming our way. Data mining provides a way of finding these insights, and Python is one of the most popular languages for data mining, providing both power and flexibility in analysis. This book teaches you to design and develop data mining applications using a variety of datasets, starting with basic classification and affinity analysis. There is a rich and varied set of libraries available in Python for data mining. This book covers a large number of these libraries, including the IPython Notebook, pandas, scikit-learn, and NLTK. You will also get hands-on experience with a text mining exercise, and see its importance in usage of modern internet. Next, we move on to more complex data types including text, images, and graphs. In every chapter, we create models that solve real-world problems. Further on, you will also discover object detection using Deep Neural Networks, which is one of the big, difficult areas of machine learning right now. With restructured examples and code samples updated for the latest edition of Python, each chapter of this book introduces you to new algorithms and techniques. By the end of the book, you will have great insights into using Python for data mining, and a good knowledge and understanding of the algorithms and implementations.