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. Python is a High-level, Procedural, and object-oriented language; it is also a vast language itself, and covering the whole of Python is one the worst mistakes we can make in the data science journey.

Data Science 75

Data Science Machine Learning Machine Learning Database 75

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

Pickl AI

APRIL 3, 2025

It involves handling missing values, correcting errors, removing duplicates, standardizing formats, and structuring data for analysis. Exploratory Data Analysis (EDA): Using statistical summaries and initial visualisations (yes, visualisation plays a role within analysis!)

Data Analysis 52

Data Analysis Data Analysis Data Visualization EDA 52

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. However, there are a few fundamental principles that remain the same throughout.

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

It acts like a table or spreadsheet where data is organised in rows and columns. Each column can hold data of different types, such as integers, floats, or strings. This structure makes DataFrames ideal for handling structured data, similar to SQL tables or Excel spreadsheets.

Data Analysis 52

Data Analysis Data Analysis Exploratory Data Analysis Python 52

Pickl AI

SEPTEMBER 12, 2024

Deep Learning : A subset of Machine Learning that uses Artificial Neural Networks with multiple hidden layers to learn from complex, high-dimensional data. Exploratory Data Analysis (EDA): Analysing and visualising data to discover patterns, identify anomalies, and test hypotheses.

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

Generative AI can be used to automate the data modeling process by generating entity-relationship diagrams or other types of data models and assist in UI design process by generating wireframes or high-fidelity mockups. 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. The role of a data scientist is changing so fast that often schools cant keep up. It depends.

Data Scientist 105

Data Scientist EDA AI AI 105