Smart Data Collective

JUNE 4, 2021

it is overwhelming to learn data science concepts and a general-purpose language like python at the same time. Exploratory Data Analysis. Exploratory data analysis is analyzing and understanding data. Deep Learning. Use cases of data science. Ensembling.

Data Science 133

Data Science Exploratory Data Analysis Machine Learning Machine Learning 133

Dataconomy

MAY 16, 2023

They employ statistical and mathematical techniques to uncover patterns, trends, and relationships within the data. Data scientists possess a deep understanding of statistical modeling, data visualization, and exploratory data analysis to derive actionable insights and drive business decisions.

Data Scientist 156

Data Scientist ML ML Machine Learning 156

Heartbeat

FEBRUARY 13, 2023

Comet is an MLOps platform that offers a suite of tools for machine-learning experimentation and data analysis. It is designed to make it easy to track and monitor experiments and conduct exploratory data analysis (EDA) using popular Python visualization frameworks.

Data Science 94

Data Science Python Deep Learning Deep Learning 94

Becoming Human

MAY 15, 2023

In programming, You need to learn two types of language. One is a scripting language such as Python, and the other is a Query language like SQL (Structured Query Language) for SQL Databases. There is one Query language known as SQL (Structured Query Language), which works for a type of database.

Data Science 75

Data Science Machine Learning Machine Learning Database 75

Pickl AI

JULY 10, 2024

Additionally, both AI and ML require large amounts of data to train and refine their models, and they often use similar tools and techniques, such as neural networks and deep learning. Inspired by the human brain, neural networks are crucial for deep learning, a subset of ML that deals with large, complex datasets.

Machine Learning 52

Machine Learning Machine Learning AI AI 52

Pickl AI

APRIL 26, 2024

This comprehensive blog outlines vital aspects of Data Analyst interviews, offering insights into technical, behavioural, and industry-specific questions. It covers essential topics such as SQL queries, data visualization, statistical analysis, machine learning concepts, and data manipulation techniques.

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52

Pickl AI

JULY 25, 2023

Data engineers are essential professionals responsible for designing, constructing, and maintaining an organization’s data infrastructure. They create data pipelines, ETL processes, and databases to facilitate smooth data flow and storage. Data Visualization: Matplotlib, Seaborn, Tableau, etc.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52