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Daniel Moura updated their profile
Sep 5, 2019
Daniel Moura posted a blog post

Julia vs R: Freeing the data scientist mind from the curse of vectoRization

Nowadays, most data scientists use either Python or R as their main programming language. That was also my case until I met Julia earlier this year. Julia promises performance comparable to statically typed compiled languages (like C) while keeping the rapid development features of interpreted languages (like Python, R or Matlab). This performance is achieved by just-in-time (JIT) compilation. Instead of interpreting code, Julia compiles code in runtime. While JIT compilation has been around…See More
Aug 22, 2019
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Daniel Moura's blog post was featured

Julia vs R: Freeing the data scientist mind from the curse of vectoRization

Nowadays, most data scientists use either Python or R as their main programming language. That was also my case until I met Julia earlier this year. Julia promises performance comparable to statically typed compiled languages (like C) while keeping the rapid development features of interpreted languages (like Python, R or Matlab). This performance is achieved by just-in-time (JIT) compilation. Instead of interpreting code, Julia compiles code in runtime. While JIT compilation has been around…See More
Aug 22, 2019
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Profile Information

Job Title:
Head of Data
Seniority:
Technical
Job Function:
Data Science, Machine Learning, AI, BI
Short Bio:
Computer Scientist and Engineer passionate about Data and Algorithms
Interests:
Contributing, Networking, Other

@daniel_c_moura

linkedin: dmoura

vimeo: danielcmoura

Daniel Moura's Blog

Julia vs R: Freeing the data scientist mind from the curse of vectoRization

Posted on August 22, 2019 at 1:00pm 0 Comments

Nowadays, most data scientists use either Python or R as their main programming language. That was also my case until I met Julia earlier this year. Julia promises performance comparable to statically typed compiled languages (like C) while keeping the rapid development features of interpreted languages (like Python, R or Matlab). This performance is achieved by just-in-time (JIT) compilation. Instead of interpreting code, Julia compiles code in runtime. While JIT compilation has…

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