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. Let’s get started.

ML 75

ML ML EDA Data Wrangling 75

DrivenData Labs

AUGUST 27, 2024

Use Open Data from Closed Prize Competitions ¶ As part of a problem set, in-class demonstration, exam, or other project assignment that requires model development, you can use the open data from a closed prize competition. On request, we can make a custom leaderboard just for your class or for different sections of your class.

Data Science 130

Data Science Algorithm Data Wrangling Machine Learning 130

Pickl AI

APRIL 21, 2025

Semi-Structured Data: Data that has some organizational properties but doesn’t fit a rigid database structure (like emails, XML files, or JSON data used by websites). Unstructured Data: Data with no predefined format (like text documents, social media posts, images, audio files, videos).

Big Data 52

Big Data Big Data Data Science Machine Learning 52

Pickl AI

NOVEMBER 4, 2024

You can create a new environment for your Data Science projects, ensuring that dependencies do not conflict. Jupyter Notebook is another vital tool for Data Science. It allows you to create and share live code, equations, visualisations, and narrative text documents.

Data Science 52

Data Science Python Machine Learning Machine Learning 52

Pickl AI

SEPTEMBER 12, 2024

D Data Mining : The process of discovering patterns, insights, and knowledge from large datasets using various techniques such as classification, clustering, and association rule learning. Data Wrangling: The cleaning, transforming, and structuring of raw data into a format suitable for analysis.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52