Julia Programming Language -
the Rising star of a new era!
Julia Programming Language - the Rising star of a new era!
By Aatmaj Mhatre
Right from my first encounter with the Julia Programming Language, I was bedazzled by its ingenious design! I still remember the day I was first introduced to the language. I was just browsing YouTube, when I came across this featured video. That was the first time I had ever heard about Julia, and I was left awestruck. Simple yet elegant, easy yet powerful. Clear syntax, lightning speed, superior parallelism - The Julia has got it all!
While being as fast as C, the language has been crafted to a developer friendly syntax. As rightly said by it’s co-founder Viral Shah, Julia is where simplicity meets speed! Julia is designed not only for numerical and scientific computing, but for building complete applications too. Most linear algebra is quicker and easier to do in Julia than other languages like Python. This is because it was specifically designed for statistics and machine-learning.
With State of Art ecosystems and optimization tools, Julia is a sweet spot for ML and DS enthusiasts! Unlike Python, Julia is a JIT compiled language, which means it is way faster than Python. (See the difference here). Here are a few reasons which makes Julia more efficient than Python.
With the growing popularity of Julia and it’s ever increasing community, it is highly likely that Julia will emerge as a powerful, simple yet efficient language. Foreign function interfaces for tens of thousands of C, Fortran, Python, and R libraries are already available. Courses like this are teaching Julia to the masses. Moreover, Julia is completely open source and free!
With a new boom in the rapid developing community, will Julia be seen as a trustable alternative to Python? Or will it, like Perl and Ruby, be written into a GoodBye World program?
By Aatmaj Mhatre
Right from my first encounter with the Julia Programming Language, I was bedazzled by its ingenious design! I still remember the day I was first introduced to the language. I was just browsing YouTube, when I came across this featured video. That was the first time I had ever heard about Julia, and I was left awestruck. Simple yet elegant, easy yet powerful. Clear syntax, lightning speed, superior parallelism - The Julia has got it all!
While being as fast as C, the language has been crafted to a developer friendly syntax. As rightly said by it’s co-founder Viral Shah, Julia is where simplicity meets speed! Julia is designed not only for numerical and scientific computing, but for building complete applications too. Most linear algebra is quicker and easier to do in Julia than other languages like Python. This is because it was specifically designed for statistics and machine-learning.
With State of Art ecosystems and optimization tools, Julia is a sweet spot for ML and DS enthusiasts! Unlike Python, Julia is a JIT compiled language, which means it is way faster than Python. (See the difference here). Here are a few reasons which makes Julia more efficient than Python.
With the growing popularity of Julia and it’s ever increasing community, it is highly likely that Julia will emerge as a powerful, simple yet efficient language. Foreign function interfaces for tens of thousands of C, Fortran, Python, and R libraries are already available. Courses like this are teaching Julia to the masses. Moreover, Julia is completely open source and free!
With a new boom in the rapid developing community, will Julia be seen as a trustable alternative to Python? Or will it, like Perl and Ruby, be written into a GoodBye World program?