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コース概要
Introduction
- SciPy vs NumPy
- Overview of SciPy features and components
Getting Started
- Installing SciPy
- Understanding basic functions
Implementing Scientific Computing
- Using SciPy constants
- Calculating integrals
- Solving linear equations
- Creating matrices with sparse and graphs
- Optimizing or minimizing functions
- Performing significance tests
- Working with different file formats (Matlab, IDL, Matrix Market, etc.)
Visualizing and Manipulating Data
- Implementing K-means clustering
- Using spatial data structures
- Processing multidimensional images
- Calculating Fourier transformations
- Using interpolation for fixed data points
Troubleshooting
Summary and Next Steps
要求
- Python programming experience
Audience
- Developers
7 時間
お客様の声 (4)
さまざまな例が非常にインタラクティブで、トレーニングの開始から終了までの間に複雑さが徐々に増していきます。
Jenny - Andheo
コース - GPU Programming with CUDA and Python
Machine Translated
例と演習
Kamil
コース - Introduction to Data Science and AI using Python
Machine Translated
examples based on our data
Witold - P4 Sp. z o.o.
コース - Deep Learning for Telecom (with Python)
That it was applying real company data. Trainer had a very good approach by making trainees participate and compete