ODSC - Open Data Science

MARCH 13, 2023

First, there’s a need for preparing the data, aka data engineering basics. Machine learning practitioners are often working with data at the beginning and during the full stack of things, so they see a lot of workflow/pipeline development, data wrangling, and data preparation.

Machine Learning 94

Machine Learning Machine Learning Data Wrangling Data Science 94

ODSC - Open Data Science

MARCH 5, 2025

He identifies several key specializations within modern datascience: Data Science & Analysis: Traditional statistical modeling and machine learning applications. Data Engineering: The infrastructure and pipeline work that supports AI and datascience. Data Management & Governance: Ensuring data quality, compliance, and security.

Data Science 52

Data Science Cloud Computing SQL Machine Learning 52

Towards AI

JUNE 25, 2024

As a Python user, I find the {pySpark} library super handy for leveraging Spark’s capacity to speed up data processing in machine learning projects. But here is a problem: While pySpark syntax is straightforward and very easy to follow, it can be readily confused with other common libraries for data wrangling.

ML 75

ML ML EDA Data Wrangling 75

Pickl AI

APRIL 21, 2025

Key Takeaways Big Data focuses on collecting, storing, and managing massive datasets. Data Science extracts insights and builds predictive models from processed data. Big Data technologies include Hadoop, Spark, and NoSQL databases. Data Science uses Python, R, and machine learning frameworks.

Big Data 52

Big Data Big Data Data Science Machine Learning 52

ODSC - Open Data Science

MARCH 24, 2025

Tomic highlighted how AI is transforming education, making coding and data analysis more accessible but also raising new challenges. Historically, data analysts were required to write SQL queries or scripts in Python to extract insights. Now, with AI-powered analytics tools, users can talk to data using natural language queries.

Analytics 52

Analytics Analytics AI AI 52

ODSC - Open Data Science

SEPTEMBER 20, 2023

Register now while tickets are 50% off. Prices go up Friday!

Data Wrangling 52

Data Wrangling Data Science Machine Learning Machine Learning 52

Dataconomy

MAY 16, 2023

Key skills and qualifications for machine learning engineers include: Strong programming skills: Proficiency in programming languages such as Python, R, or Java is essential for implementing machine learning algorithms and building data pipelines.

Data Scientist 156

Data Scientist ML ML Machine Learning 156