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    freeCodeCamp - Data Analysis with Python

    freeCodeCamp - Data Analysis with Python

    In these comprehensive video courses, created by Santiago Basulto, you will learn the whole process of data analysis. You'll be reading data from multiple sources (CSV, SQL, Excel), process that data using NumPy and Pandas, and visualize it using Matplotlib and Seaborn, Additionally, we've included a thorough Jupyter Notebook course, and a quick Python reference to refresh your programming skills.

    Course related:
    AMA1600 Fundamentals of AI and Data Analytics and AMA1751 Linear Algebra
    Subjects:
    Mathematics and Statistics and Computing
    Keywords:
    Computer programming Computer science Python (Computer program language)
    Resource Type:
    Others
     
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    Nick Higham: Applied Mathematics, Numerical Linear Algebra and Software

    Nick Higham: Applied Mathematics, Numerical Linear Algebra and Software

    Nicholas John Higham FRS is a British numerical analyst. He is Royal Society Research Professor and Richardson Professor of Applied Mathematics in the School of Mathematics at the University of Manchester. In this blog, it covers the popular topic, such as:

    (1) Top 5 Beamer Tips

    (2) The Nearest Correlation Matrix

    (3) The Top 10 Algorithms in Applied Mathematics

    (4) A Black Background for More Restful PDF viewing

    (5) Typesetting Mathematics According to the ISO Standard

    (6) Fourth Edition (2013) of Golub and Van Loan’s Matrix Computations

    (7) The Rise of Mixed Precision Arithmetic

    (8) Second Edition (2013) of Matrix Analysis by Horn and Johnson

    (9) Half Precision Arithmetic: fp16 Versus bfloat16

    (10) Managing BibTeX Files with Emacs

    (11) Five Examples of Proofreading

    (12) Implicit Expansion: A Powerful New Feature of MATLAB R2016b

    (13) Dot Grid Paper for Writing Mathematics

    (14) Programming Languages: An Applied Mathematics View

    (15) Three BibTeX Tips

    (16) Better LaTeX Tables with Booktabs

    (17) The Princeton Companion to Applied Mathematics

    (18) Numerical Methods That (Usually) Work

    (19) What’s New in MATLAB R2017a?

    (20) What Is Numerical Stability?


    Course related:
    AMA615 Nonlinear Optimization Methods and AMA611 Applied Analysis
    Subjects:
    Mathematics and Statistics
    Keywords:
    Computer programming Numerical analysis
    Resource Type:
    Others