Clojure
Modern Lisp for JVM with emphasis on immutable data
Data Science
Data analysis and statistics
Pros and Cons
Ventajas
- + High demand and good salaries
- + Direct impact on decisions
- + Very active community
Desventajas
- - Requires mathematical foundations
- - Critical data quality
- - Results difficult to communicate
Recommended Languages
11 popular languages in Data Science
Fortran
Historic language optimized for scientific numerical computing
F#
Microsoft's functional-first language for .NET
Julia
High-performance language for scientific computing
MATLAB
Proprietary language for numerical computing and simulation
Mojo
Modular's language combining Python with systems performance
Perl
Classic language for text processing and scripting
Prolog
Logic programming language for AI and expert systems
Python
Versatile language for web, data and AI with clear syntax
R
Specialized language for statistics and data science
SQL
Standard language for relational databases
Frameworks and Tools
12 popular frameworks
Apache Airflow
Data workflow orchestration platform
CesiumJS
JavaScript engine for 3D globes and maps
Dagster
Modern data orchestrator with assets-first approach
Dash
Python framework for analytical web applications
Gradio
Framework to create user interfaces for ML models
Kedro
ML pipeline framework with engineering best practices
PostgreSQL
Advanced open source relational database with SQL support and extensibility
Prefect
Modern workflow automation platform
PyTorch
Deep learning framework preferred in research
Ray
Distributed computing framework for ML and Python
Streamlit
Python framework to quickly create data science apps
TensorFlow
Google's ML framework for production