Search results
Results From The WOW.Com Content Network
Design philosophy and features. Python is a multi-paradigm programming language. Object-oriented programming and structured programming are fully supported, and many of their features support functional programming and aspect-oriented programming (including metaprogramming [68] and metaobjects ). [69]
Anaconda is a distribution of the Python and R programming languages for scientific computing ( data science, machine learning applications, large-scale data processing, predictive analytics, etc.), that aims to simplify package management and deployment. The distribution includes data-science packages suitable for Windows, Linux, and macOS.
Data science is an interdisciplinary field [10] focused on extracting knowledge from typically large data sets and applying the knowledge and insights from that data to solve problems in a wide range of application domains. The field encompasses preparing data for analysis, formulating data science problems, analyzing data, developing data ...
SciPy (pronounced / ˈsaɪpaɪ / "sigh pie" [2]) is a free and open-source Python library used for scientific computing and technical computing. [3] SciPy contains modules for optimization, linear algebra, integration, interpolation, special functions, FFT, signal and image processing, ODE solvers and other tasks common in science and engineering.
Timsort is a stable sorting algorithm (order of elements with same key is kept) and strives to perform balanced merges (a merge thus merges runs of similar sizes). In order to achieve sorting stability, only consecutive runs are merged. Between two non-consecutive runs, there can be an element with the same key inside the runs.
The Zen of Python is a collection of 19 "guiding principles" for writing computer programs that influence the design of the Python programming language. Python code that aligns with these principles is often referred to as "Pythonic". Software engineer Tim Peters wrote this set of principles and posted it on the Python mailing list in 1999.
Genre. Mathematics, problem solving. Publication date. 1945. ISBN. 9780691164076. How to Solve It (1945) is a small volume by mathematician George Pólya, describing methods of problem solving. [1] This book has remained in print continually since 1945.
In particular, three data sets are commonly used in different stages of the creation of the model: training, validation, and test sets. The model is initially fit on a training data set, [3] which is a set of examples used to fit the parameters (e.g. weights of connections between neurons in artificial neural networks) of the model. [4]