Zu seinem Ergebnis. In Python erlauben Funktionen wie map, filter und reduce, aber auch list comprehensions funktionales Programmieren. In C ist funktionales Programmieren aufgrund des Fehlens einer automatischen Speicherverwaltung (und auch eines vern¨unftigen eingebauten Sequenztyps) eher schwierig. Programmieren Lernen.pdf - Free download Ebook, Handbook, Textbook, User Guide PDF files on the internet quickly and easily. Programmieren In Java Android Studio Programmieren Android-apps Programmieren Neuronale Netze Programmieren Neuronale Netze Programmieren Mit Python Neuronale Netze Selbst Programmieren Pdf Neuronale Netze Selbst.
Rich Ecosystem for Scientific Computing
Julia is designed from the ground up to be very good at numerical and scientific computing. This can be seen in the abundance of scientific tooling written in Julia, such as the state-of-the-art differential equations ecosystem (DifferentialEquations.jl), optimization tools (JuMP.jl and Optim.jl), iterative linear solvers (IterativeSolvers.jl), a robust framework for Fourier transforms (AbstractFFTs.jl), a general purpose quantum simulation framework (Yao.jl), and many more, that can drive all your simulations.
Julia also offers a number of domain-specific ecosystems, such as in biology (BioJulia), operations research (JuliaOpt), image processing (JuliaImages), quantum physics (QuantumBFS, QuantumOptics), nonlinear dynamics (JuliaDynamics), quantitative economics (QuantEcon), astronomy (JuliaAstro) and ecology (EcoJulia). With a set of highly enthusiastic developers and maintainers from various parts of the scientific community, this ecosystem will only continue to get bigger and bigger.