Yuxing Yan - Hands-On Data Science with Anaconda

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Dr. Yuxing Yan graduated from McGill University with a PhD in finance. He has taught various finance courses at eight universities in Canada, Singapore, and the U.S. He has published 23 research and teaching-related papers, and is the author of 6 books. Two of his recent publications are Python for Finance and Financial Modelling using R. He is well-versed in R, Python, SAS, MATLAB, Octave, and C. In addition, he is an expert on financial data analytics.

James Yan is an undergraduate student at the University of Toronto (UofT), currently double-majoring in computer science and statistics. He has hands-on knowledge of Python, R, Java, MATLAB , and SQL. During his study at UofT, he has taken many related courses, such as Methods of Data Analysis I and II, Methods of Applied Statistics, Introduction to Databases, Introduction to Artificial Intelligence, and Numerical Methods, including a capstone course on AI in clinical medicine.

Justin (Byung Uk) Lee completed his BA and master's in computer science at KAIST. He developed Korean Windows CE 1.0 and 2.0 at Microsoft while working for LG Electronics. Later, he ran his own business for more than 7 years, which proposed custom-tailored financial portfolios derived from data analysis. He then worked for several life and non-life insurers, including Samsung Life as a CMO and CSMO conducting CRM-based marketing. Currently, he intensively researches machine learning based big data finance analysis and financial applications using blockchain.

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Anaconda is an open source data science platform that brings the best tools for data science together. It is a data science stack that includes more than 100 popular packages based on Python, Scala, and R. With the help of its package manager, conda, users can work with hundreds of packages in different languages and perform data preprocessing, modeling, clustering, classification, and validation with ease.

This book will get you started with Anaconda and how you can use it to perform data science operations in the real world. You will start of setting up the environment for the Anaconda platform, Jupyter, and installing the relevant packages. You will then cover the basics of data science and linear algebra for performing data science tasks. Once you are ready to go, you will start with data science operations such as cleaning, sorting, and data classification. You will then learn how to perform tasks such as clustering, regression, prediction, building machine learning models, and optimizing them. You will also learn how to visualize data and share the projects.