Remove Cloud Computing Remove Clustering Remove EDA
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Leveraging IBM Cloud for electronic design automation (EDA) workloads

IBM Journey to AI blog

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
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Data Science Career FAQs Answered: Educational Background

Mlearning.ai

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.

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Top 10 Data Science Interviews Questions and Expert Answers

Pickl AI

Clustering algorithms such as K-means and hierarchical clustering are examples of unsupervised learning techniques. What is the Central Limit Theorem, and why is it important in statistics? How do you handle missing values in a dataset? Handling missing values is a critical aspect of data preprocessing.

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Roadmap to Learn Data Science for Beginners and Freshers in 2023

Becoming Human

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.