Scipython notes (04) (Tính toán Khoa học trong Python) - Sebastian Raschka
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Tài liệu bài giảng môn STAT 479: Machine Learning của Sebastian Raschka tại Đại học Wisconsin–Madison, chương 4 về Tính toán Khoa học trong Python, bao gồm NumPy, SciPy, Matplotlib.
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STAT 479: Machine Learning Lecture Notes Sebastian Raschka Department of Statistics University of Wisconsin–Madison http://stat.wisc.edu/∼sraschka/teaching/stat479-fs2018/ Fall 2018 Contents 4 Scientific Computing in Python 4.1 2 NumPy – Working with Numerical Arrays . . . . . . . . . . . . . . . . . . . . 2 4.1.1 Introduction to NumPy . . . . . . . . . . . . . . . . . . . . . . . . . . 2 4.1.2 N-dimensional Arrays . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 4.1.3 Array Construction Routines . . . . . . . . . . . . . . . . . . . . . . . 4 4.1.4 Array Indexing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 4.1.5 Array Math and Universal Functions . . . . . . . . . . . . . . . . . . . 7 4.1.6 Broadcasting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 4.1.7 Advanced Indexing – Memory Views and Copies . . . . . . . . . . . . 10 4.1.8 Random Number Generators . . . . . . . . . . . . . . . . . . . . . . . 13 4.1.9 Reshaping Arrays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 4.1.10 Comparison Operators and Masks . . . . . . . . . . . . . . . . . . . . 15 4.1.11 Linear Algebra with NumPy Arrays . . . . . . . . . . . . . . . . . . . 16 4.2 SciPy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 4.3 Matplotlib . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 4.3.1 Plotting Functions and Lines . . . . . . . . . . . . . . . . . . . . . . . 20 4.3.2 Scatter Plots . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 4.3.3 Bar Plots . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 4.3.4 Histograms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 4.3.5 Subplots . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 4.3.6 Colors and Markers . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 4.3.7 4.4 Saving Plots . . . . . . . .
AI summary
- Document name
- Scipython notes (04) (Tính toán Khoa học trong Python) - Sebastian Raschka
- School / Course
- University Wisconsin-Madison · Machine learning
- Content
- Tài liệu giới thiệu về tính toán khoa học trong Python, tập trung vào thư viện NumPy để xử lý mảng đa chiều, SciPy cho các chức năng khoa học, và Matplotlib để trực quan hóa dữ liệu.
- Table of contents
- 4 Scientific Computing in Python
- 4.1 NumPy – Working with Numerical Arrays
- 4.1.1 Introduction to NumPy
- 4.1.2 N-dimensional Arrays
- 4.1.3 Array Construction Routines
- 4.1.4 Array Indexing
- 4.1.5 Array Math and Universal Functions
- 4.1.6 Broadcasting
- 4.1.7 Advanced Indexing – Memory Views and Copies
- 4.1.8 Random Number Generators
- 4.1.9 Reshaping Arrays
- 4.1.10 Comparison Operators and Masks
- 4.1.11 Linear Algebra with NumPy Arrays
- 4.2 SciPy
- 4.3 Matplotlib
- 4.3.1 Plotting Functions and Lines
- 4.3.2 Scatter Plots
- 4.3.3 Bar Plots
- 4.3.4 Histograms
- 4.3.5 Subplots
- 4.3.6 Colors and Markers
- 4.3.7 Saving Plots
- 4.4 Resources
- Pages
- 26 pages
- Uploaded by
- Uni24h
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Scipython notes (04) (Tính toán Khoa học trong Python) - Sebastian Raschka
Generating preview...
STAT 479: Machine Learning Lecture Notes Sebastian Raschka Department of Statistics University of Wisconsin–Madison http://stat.wisc.edu/∼sraschka/teaching/stat479-fs2018/ Fall 2018 Contents 4 Scientific Computing in Python 4.1 2 NumPy – Working with Numerical Arrays . . . . . . . . . . . . . . . . . . . . 2 4.1.1 Introduction to NumPy . . . . . . . . . . . . . . . . . . . . . . . . . . 2 4.1.2 N-dimensional Arrays . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 4.1.3 Array Construction Routines . . . . . . . . . . . . . . . . . . . . . . . 4 4.1.4 Array Indexing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 4.1.5 Array Math and Universal Functions . . . . . . . . . . . . . . . . . . . 7 4.1.6 Broadcasting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 4.1.7 Advanced Indexing – Memory Views and Copies . . . . . . . . . . . . 10 4.1.8 Random Number Generators . . . . . . . . . . . . . . . . . . . . . . . 13 4.1.9 Reshaping Arrays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 4.1.10 Comparison Operators and Masks . . . . . . . . . . . . . . . . . . . . 15 4.1.11 Linear Algebra with NumPy Arrays . . . . . . . . . . . . . . . . . . . 16 4.2 SciPy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 4.3 Matplotlib . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 4.3.1 Plotting Functions and Lines . . . . . . . . . . . . . . . . . . . . . . . 20 4.3.2 Scatter Plots . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 4.3.3 Bar Plots . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 4.3.4 Histograms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 4.3.5 Subplots . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 4.3.6 Colors and Markers . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 4.3.7 4.4 Saving Plots . . . . . . . .
Read full document
- Document name
- Scipython notes (04) (Tính toán Khoa học trong Python) - Sebastian Raschka
- School / Course
- University Wisconsin-Madison · Machine learning
- Content
- Tài liệu giới thiệu về tính toán khoa học trong Python, tập trung vào thư viện NumPy để xử lý mảng đa chiều, SciPy cho các chức năng khoa học, và Matplotlib để trực quan hóa dữ liệu.
- Table of contents
- 4 Scientific Computing in Python
- 4.1 NumPy – Working with Numerical Arrays
- 4.1.1 Introduction to NumPy
- 4.1.2 N-dimensional Arrays
- 4.1.3 Array Construction Routines
- 4.1.4 Array Indexing
- 4.1.5 Array Math and Universal Functions
- 4.1.6 Broadcasting
- 4.1.7 Advanced Indexing – Memory Views and Copies
- 4.1.8 Random Number Generators
- 4.1.9 Reshaping Arrays
- 4.1.10 Comparison Operators and Masks
- 4.1.11 Linear Algebra with NumPy Arrays
- 4.2 SciPy
- 4.3 Matplotlib
- 4.3.1 Plotting Functions and Lines
- 4.3.2 Scatter Plots
- 4.3.3 Bar Plots
- 4.3.4 Histograms
- 4.3.5 Subplots
- 4.3.6 Colors and Markers
- 4.3.7 Saving Plots
- 4.4 Resources
- Pages
- 26 pages
- Uploaded by
- Uni24h
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