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Daniel Moura updated their profile
Sep 5
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
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

Profile Information

Short Bio
Computer Scientist and Engineer passionate about Data and Algorithms
Field of Expertise
Data Science, Machine Learning, AI, BI
Professional Status
Technical
Years of Experience:
20
Your Job Title:
Head of Data
How did you find out about DataScienceCentral?
Twitter
Interests:
Contributing, Networking, Other

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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