IBM Journey to AI blog

OCTOBER 31, 2023

Electronic design automation (EDA) is a market segment consisting of software, hardware and services with the goal of assisting in the definition, planning, design, implementation, verification and subsequent manufacturing of semiconductor devices (or chips). The primary providers of this service are semiconductor foundries or fabs.

EDA 100

EDA Cloud Computing Clustering Artificial Intelligence 100

IBM Journey to AI blog

JUNE 4, 2024

The role of cloud in HPC Most commonly, enterprises that run workloads with surges in activity are finding that they exceed the compute capacity available on-premises. This is an example of where cloud computing can augment on-premises HPC to transform the business’s approach to HPC with cloud resources.

EDA 100

EDA Cloud Computing Machine Learning Machine Learning 100

IBM Journey to AI blog

NOVEMBER 6, 2023

Over the past decade, we’ve seen serverless computing take the cloud computing world by storm. Serverless is a cloud computing application development and execution model that enables developers to build and run application code without provisioning or managing servers or backend infrastructure.

Cloud Computing 134

Cloud Computing Database EDA AI 134

Hacker News

SEPTEMBER 15, 2024

Saidi: One thing that’s very interesting for AWS is that we’re the cloud and we’re also developing these chips in the cloud. We were the first company to really push on running [electronic design automation (EDA)] in the cloud. If I want, tomorrow I can have 300. The next day, I can have 1,000.”

AWS 181

AWS EDA Machine Learning Machine Learning 181

Mlearning.ai

MAY 23, 2023

This includes skills in data cleaning, preprocessing, transformation, and exploratory data analysis (EDA). Check out this course to upskill on Apache Spark —  [link] Cloud Computing technologies such as AWS, GCP, Azure will also be a plus. Familiarity with libraries like pandas, NumPy, and SQL for data handling is important.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Becoming Human

MAY 15, 2023

For Data Analysis you can focus on such topics as Feature Engineering , Data Wrangling , and EDA which is also known as Exploratory Data Analysis. First learn the basics of Feature Engineering, and EDA then take some different-different data sheets (data frames) and apply all the techniques you have learned to date.

Data Science 75

Data Science Machine Learning Machine Learning Database 75

Pickl AI

FEBRUARY 12, 2024

What is the Central Limit Theorem, and why is it important in statistics?

Data Science 52

Data Science Cross Validation Machine Learning Machine Learning 52