Becoming Human

MAY 15, 2023

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. SQL Databases are MySQL , PostgreSQL , MariaDB , etc.

Data Science 75

Data Science Machine Learning Machine Learning Database 75

Mlearning.ai

MAY 23, 2023

This includes skills in data cleaning, preprocessing, transformation, and exploratory data analysis (EDA). 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

Pickl AI

JULY 25, 2023

With expertise in programming languages like Python , Java , SQL, and knowledge of big data technologies like Hadoop and Spark, data engineers optimize pipelines for data scientists and analysts to access valuable insights efficiently. Excel, Tableau, Power BI, SQL Server, MySQL, Google Analytics, etc.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Pickl AI

APRIL 3, 2025

Exploratory Data Analysis (EDA): Using statistical summaries and initial visualisations (yes, visualisation plays a role within analysis!) EDA: Calculate overall churn rate. Visualisation Aids Analysis Visualisation is not just an end product; it’s a crucial tool during analysis (especially EDA).

Data Analysis 52

Data Analysis Data Analysis Data Visualization EDA 52

Heartbeat

FEBRUARY 13, 2023

It is designed to make it easy to track and monitor experiments and conduct exploratory data analysis (EDA) using popular Python visualization frameworks. The SQL database used by Kangas Datagrid enables users to keep many datasets. This can save time and make working with large datasets more efficient.

Data Science 94

Data Science Python Deep Learning Deep Learning 94

Dataconomy

AUGUST 16, 2023

Exploratory Data Analysis (EDA) : Like intrepid explorers wandering through an uncharted forest, data scientists traverse the terrain of data with curiosity. Utilizes tools like SQL and Excel for data manipulation and report creation. Interprets data to uncover actionable insights guiding business decisions.

Data Scientist 172

Data Scientist Data Science Machine Learning Machine Learning 172

IBM Journey to AI blog

OCTOBER 15, 2024

The combination of high CPU performance and high memory footprint makes R7iz instances suited for front-end Electronic Design Automation (EDA), relational database workloads with high per-core licensing fees, and financial, actuarial and data analytics simulation workloads.

AWS 45

AWS Data Lakes EDA Database 45

Dataconomy

JULY 28, 2023

Exploratory data analysis (EDA) Before preprocessing data, conducting exploratory data analysis is crucial to understand the dataset’s characteristics, identify patterns, detect outliers, and validate missing values. EDA provides insights into the data distribution and informs the selection of appropriate preprocessing techniques.

Power BI 91

Power BI Data Preparation Exploratory Data Analysis Machine Learning 91

AWS Machine Learning Blog

MAY 30, 2023

You can build custom queries to look up AWS CUR data using standard SQL. For ML model development, the size of a SageMaker notebook instance depends on the amount of data you need to load in-memory for meaningful exploratory data analyses (EDA) and the amount of computation required. For example, ml.t2.medium

AWS 90

AWS ML ML EDA 90

Pickl AI

FEBRUARY 12, 2024

Here are some key areas often assessed: Programming Proficiency Candidates are often tested on their proficiency in languages such as Python, R, and SQL, with a focus on data manipulation, analysis, and visualization. However, there are a few fundamental principles that remain the same throughout. Here is a brief description of the same.

Data Science 52

Data Science Cross Validation Machine Learning Machine Learning 52

ODSC - Open Data Science

AUGUST 9, 2023

Step 1: Importing the Necessary Libraries The first step involves importing the necessary libraries, including PySpark SQL functions and types import pyspark.sql.functions as F import pyspark.sql.types as T from pyspark.ml.feature import Imputer, MinMaxScaler, VectorAssembler Step 2: Data Preprocessing and EDA (Exploratory Data Analysis) We load the (..)

Machine Learning 52

Machine Learning Machine Learning AWS Big Data 52

Pickl AI

AUGUST 14, 2024

This structure makes DataFrames ideal for handling structured data, similar to SQL tables or Excel spreadsheets. Data Analysis : Performing exploratory data analysis (EDA) to understand patterns, trends, and relationships in the data. It acts like a table or spreadsheet where data is organised in rows and columns.

Data Analysis 52

Data Analysis Data Analysis Exploratory Data Analysis Python 52

Pickl AI

SEPTEMBER 12, 2024

Exploratory Data Analysis (EDA): Analysing and visualising data to discover patterns, identify anomalies, and test hypotheses. Query: A request for information or data retrieval from a database, often written in a structured query language (SQL).

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52

AWS Machine Learning Blog

AUGUST 12, 2024

AWS data engineering pipeline The adaptable approach detailed in this post starts with an automated data engineering pipeline to make data stored in Splunk available to a wide range of personas, including business intelligence (BI) analysts, data scientists, and ML practitioners, through a SQL interface.

ML 109

ML ML AWS AI 109

Mlearning.ai

JUNE 16, 2023

ChatGPT and Software Architecture user story, data model in markdown table format, data model in mermaid format, sql, sequence diagram, class design adhering to solid principle Using ChatGPT to build System Diagrams — Part I Generate Mermaid.js GPT-4 Data Pipelines: Transform JSON to SQL Schema Instantly Blockstream’s public Bitcoin API.

AI 52

AI AI Data Analysis Data Analysis 52

Towards AI

JANUARY 22, 2025

Uncomfortable reality: In the era of large language models (LLMs) and AutoML, traditional skills like Python scripting, SQL, and building predictive models are no longer enough for data scientist to remain competitive in the market. Universities still mostly focus on things like EDA, data cleaning, and building/fine-tune models.

Data Scientist 105

Data Scientist EDA AI AI 105