WebIncoming political science grad student with interests in IR, comparative politics, game theory and strategic interaction. Open-source developer and competitive programmer, proficient in C/C++, Python, Julia, R, Stata; Self-learning Golang, Tensorflow and Jamstack web development. Looking for research opportunities in quantitative social sciences. … WebI’m passionate about the future. The bleeding edge tech under development is already changing the way we percibe the reality and I believe it’s going to make this the best human kind era. As I used to say: “there is no science without fiction”. Nowadays I’m passionate to contribute erasing the line between reality and fiction. I’m a multidisciplinary …
Which programming language is best for economic research: Julia …
Let us consider the problem of membership testing on an unsorted vector of integers. In principle, this problem is solved via linear search. The algorithm runs through the elements of the input vector until finding the value being searched (successful search) or reaching the end of the vector (unsuccessful search). The … See more I implemented the linear search in C to get a grasp on what would be the performance on a statically typed compiled language and to set the baseline. The binary executable took 0.26 … See more In Julia, I included a couple more flavors to show the diversity and performance of natively available functionalities. Except for vectorized operations, the performance was pretty close to the implementation in C, with a degradation … See more I tried different flavors of the membership test in R, from a specialized operator (in) to a C-like implementation using loops, passing by a … See more To be honest, the initial goal was to use only native functions and native data structures, but the inoperator was ~10x slower than R when using Python’s native lists. So, I also … See more WebPython: Good for small- or medium-scale projects to build models and analyze data, especially for fast start-ups or small teams. Scala/Java: Good for robust programming with many developers and teams; it has fewer machine learning utilities than Python and R, but it makes up for it with increased code maintenance. florida real estate offers
Comparing Python, R and Julia execution time in two contexts ... - Medium
WebAug 12, 2024 · In fact, according to a new survey, Python was named as the number one language that developers would be using if they weren't using Julia. In this blog, we explore Julia vs Python and what may be the best choice for you. 1. Speed. Julia is as fast as C. It is built for speed since the founders wanted something ‘fast’. WebPython is a high level, object-oriented language, and is easier to learn than R. When it comes to learning, SAS is the easiest to learn, followed by Python and R. 2. Data Handling Ability. Data is increasing in size and complexity every day. A data science tool must be able to store and organize large amounts of data effectively. WebAug 17, 2024 · Julia is faster than Python and R because it is specifically designed to quickly implement the basic mathematics that underlies most data science, like matrix … florida real estate offer page