sparklyr.sedona: A sparklyr extension for analyzing geospatial data
We are excited to announce the availability of sparklyr.sedona, a sparklyr extension making geospatial functionalities of the Apache Sedona library easily accessible from R.
We are excited to announce the availability of sparklyr.sedona, a sparklyr extension making geospatial functionalities of the Apache Sedona library easily accessible from R.
In this episode of Open Source Directions, we were joined by Thomas Wiecki once again who talked about the work being done with PyMC. PyMC3 is a Python package for Bayesian statistical modeling and Probabilistic Machine Learning focusing on advanced Markov chain Monte Carlo (MCMC) and variational inference (VI) algorithms. Its flexibility and extensibility make it applicable to a large suite of problems.
The field of Artificial Intelligence (AI) and Machine Learning (ML) has seen remarkable growth in recent years, shaping various industries and transforming the way we interact with technology. Open-source technologies have played a pivotal role in democratizing AI/ML, making cutting-edge tools accessible to developers and researchers worldwide. In this article, we will explore 100 open-source AI and ML technologies that are driving innovation and advancement in the field. Let’s delve into the list and discover why they are used.
As of 2023, the field of Artificial Intelligence (AI) and Machine Learning (ML) has witnessed rapid growth, innovation, and adoption across various industries. Many individuals have played pivotal roles in shaping and advancing this dynamic field. These influencers have made significant contributions through their groundbreaking research, influential publications, thought leadership, and active participation in the AI/ML community. In this article, we will highlight 124 AI and ML technology influencers who have had a profound impact on the industry.
Data science is an ever-evolving field that relies heavily on data tools and libraries to process, analyze, and visualize massive datasets. As the demand for data-driven insights continues to grow, data scientists need powerful tools and libraries that can handle complex computations efficiently. In this article, we will explore the top 50 data tools and libraries for data science, based on information from various sources such as Analytics Insight, Simplilearn, and DataCamp.
In this episode of Open Source Directions, we were joined by Aaron Meurer who will talk once again with Oscar Benjamin about the work he has been doing with SymPy. SymPy is a Python library for symbolic mathematics. It aims to become a full-featured computer algebra system (CAS) while keeping the code as simple as possible in order to be comprehensible and easily extensible. SymPy is written entirely in Python.