Advanced NumPy - SciPy Japan 2019 Tutorial - Juan Nunuz-Iglesias
Offered By: YouTube
Course Description
Overview
Dive into advanced NumPy techniques in this comprehensive tutorial from SciPy Japan 2019. Master broadcasting rules, explore strides and stride tricks, and learn advanced indexing methods. Work hands-on with practical examples using Jupyter Notebook, analyzing gene expression data, and manipulating NumPy arrays. Tackle exercises on reads per kilobase, RAM usage, transposing, slicing, and variance calculation. Gain valuable insights from Juan Nunez-Iglesias, a Research Fellow, core developer of scikit-image, and co-author of "Elegant SciPy". Enhance your Python and array computing skills to take your data analysis capabilities to the next level.
Syllabus
Introduction
Jupiter Notebook
Gene Expression
Expression Data
NumPy Array
Reads per kilobase
RAM
Transpose
Slicing
Exercises
Variance
Broadcasting
Taught by
Enthought
Related Courses
Computational Investing, Part IGeorgia Institute of Technology via Coursera Введение в машинное обучение
Higher School of Economics via Coursera Математика и Python для анализа данных
Moscow Institute of Physics and Technology via Coursera Introduction to Python for Data Science
Microsoft via edX Using Python for Research
Harvard University via edX