Data Science Dojo

MAY 1, 2023

The package is particularly well-suited for working with tabular data, such as spreadsheets or SQL tables, and provides powerful data cleaning, transformation, and wrangling capabilities. Scikit-learn Scikit-learn is a powerful library for machine learning in Python.

Python 311

Python Machine Learning Machine Learning Data Science 311

Data Science Dojo

MAY 1, 2023

The package is particularly well-suited for working with tabular data, such as spreadsheets or SQL tables, and provides powerful data cleaning, transformation, and wrangling capabilities. Scikit-learn Scikit-learn is a powerful library for machine learning in Python.

Python 195

Python Machine Learning Machine Learning Data Science 195

AWS Machine Learning Blog

JANUARY 17, 2024

We can analyze activities by identifying stops made by the user or mobile device by clustering pings using ML models in Amazon SageMaker. A cluster of pings represents popular spots where devices gathered or stopped, such as stores or restaurants. Manually managing a DIY compute cluster is slow and expensive.

Clustering 134

Clustering AWS ML ML 134

Pickl AI

FEBRUARY 12, 2024

Technical Proficiency Data Science interviews typically evaluate candidates on a myriad of technical skills spanning programming languages, statistical analysis, Machine Learning algorithms, and data manipulation techniques. Examples include linear regression, logistic regression, and support vector machines.

Data Science 52

Data Science Cross Validation Machine Learning Machine Learning 52

Pickl AI

AUGUST 9, 2024

Some of the most notable technologies include: Hadoop An open-source framework that allows for distributed storage and processing of large datasets across clusters of computers. Understanding the differences between SQL and NoSQL databases is crucial for students.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

Pickl AI

MAY 31, 2023

Explore Machine Learning with Python: Become familiar with prominent Python artificial intelligence libraries such as sci-kit-learn and TensorFlow. Begin by employing algorithms for supervised learning such as linear regression , logistic regression, decision trees, and support vector machines.

Data Science 52

Data Science Python Data Scientist Machine Learning 52

ODSC - Open Data Science

JANUARY 7, 2025

While knowing Python, R, and SQL is expected, youll need to go beyond that. Similar to previous years, SQL is still the second most popular skill, as its used for many backend processes and core skills in computer science and programming. Employers arent just looking for people who can program.

Data Scientist 40

Data Scientist Data Science Machine Learning Machine Learning 40