equations, and stability analysis This text introduces platform-independent numerical programming using Python and C/C++, and appeals to advanced undergraduate and graduate students in natural sciences and engineering, researchers involved in scientific computing, and engineers carrying out applicative ...
Quantitative thought is a technique that transforms abstract theories into concrete numerical models. This method is widely applied in various fields, including finance, engineering, and scientific research. The core of quantitative thought lies in using data analysis and model building to predict and ...
We will be using python as the programming language for this course. Python has a few advantages: Python is a general purpose programming language that is widely used in industry and at national and international research laboratories. Python is free and will be available after you graduate from...
Python: Core programming language. ALPSQuTip: A library intended to bridge the gap between ALPS condensed matter models and QuTiP calculations. ALPS: A collection of libraries for solving models in condensed matter physics, focusing on quantum many-body systems. QuTiP: For quantum computing simulation...
Furthermore, by using NumPy’s built-in high-level mathematical functions, we can quickly perform numerical analysis on an image. SciPy Going hand-in-hand with NumPy, we also have SciPy. SciPy adds further support for scientific and technical computing. One of my favorite sub-packages of ...
Quantum computing is moving beyond its early stage and seeking for commercial applications in chemical and biomedical sciences. In the current noisy intermediate-scale quantum computing era, the quantum resource is too scarce to support these exploration
A robust alternative to k-means is PAM, which is based on medoids. As discussed in the next chapter, the PAM clustering can be computed using the functionpam() [clusterpackage]. The functionpamk( ) [fpc package] is a wrapper for PAM that also prints the suggested number of clusters bas...
The first step when using k-means clustering is to indicate the number of clusters (k) that will be generated in the final solution. The algorithm starts by randomly selecting k objects from the data set to serve as the initial centers for the clusters. The selected objects are also ...
Installing the Python data stack on Mac OS X and Linux Getting ready How to do it... How it works... There's more... See also Installing extra Python packages Getting ready How to do it... How it works... There's more... See also Installing and using virtualenv Getting ready How...
Ifyouareanaspiringdatascientistwhowantstolearndatascienceandnumericalprogrammingconceptsthroughhands-on,real-worldprojectexamples,thisisthebookforyou.Whetheryouarebrandnewtodatascienceoryouareaseasonedexpert,youwillbenefitfromlearningaboutthestructureofreal-worlddatascienceprojectsandtheprogrammingexamplesinRandPython. ...