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TOWARDS DATA SCIENCE


YOUR HOME FOR DATA SCIENCE. A MEDIUM PUBLICATION SHARING CONCEPTS, IDEAS AND
CODES.


Editors' PicksFeaturesDeep DivesLatestAboutAuthor Resources
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Mastering the Art of Pricing Optimization — A Data Science Solution
MASTERING THE ART OF PRICING OPTIMIZATION — A DATA SCIENCE SOLUTION

Unlocking Secrets of Real-World Data Science Solutions for Pricing Optimization
in Retail
Rhydham Gupta
Aug 28
A bird’s eye view of linear algebra: the basics
A BIRD’S EYE VIEW OF LINEAR ALGEBRA: THE BASICS

We think basis-free, we write basis-free, but when the chips are down we close
the office door and compute with matrices like fury.
Rohit Pandey
Aug 27
Latest
Teaching Language Models to use Tools
TEACHING LANGUAGE MODELS TO USE TOOLS

Using tools makes us more capable as humans. Is the same true of LLMs?
Cameron R. Wolfe, Ph.D.
Aug 27
Build a Better Bar Chart with This Trick
BUILD A BETTER BAR CHART WITH THIS TRICK

(It’s really a seaborn scatter plot!)
Lee Vaughan
Aug 26
How to Use Chat-GPT and Python to Build a Knowledge Graph in Neo4j Based on Your
Own Articles
HOW TO USE CHAT-GPT AND PYTHON TO BUILD A KNOWLEDGE GRAPH IN NEO4J BASED ON YOUR
OWN ARTICLES

A graph containing structured knowledge from more than 120 articles on
mathematics and data science
Kasper Müller
Aug 26
Monte Carlo Methods
MONTE CARLO METHODS

An Introduction to Reinforcement Learning: Part 4
Steve Roberts
Aug 26
The CLIP Foundation Model
THE CLIP FOUNDATION MODEL

Paper Summary— Learning Transferable Visual Models From Natural Language
Supervision
Sascha Kirch
Aug 26
How to Debug Python Scripts with the Logging Module
HOW TO DEBUG PYTHON SCRIPTS WITH THE LOGGING MODULE

Print statements can only take you so far…
Aashish Nair
Aug 26
Randomizing Very Large Datasets
RANDOMIZING VERY LARGE DATASETS

Consider the problem of randomizing a dataset that is so large, it doesn’t even
fit into memory. This article describes how you can do it…
Douglas Blank, PhD
Aug 26
Effective coding with dates and times in Python
EFFECTIVE CODING WITH DATES AND TIMES IN PYTHON

Making use of datetime, zoneinfo, dateutil and pandas
Alicia Horsch
Aug 26
Dynamic Pricing with Reinforcement Learning from Scratch: Q-Learning
DYNAMIC PRICING WITH REINFORCEMENT LEARNING FROM SCRATCH: Q-LEARNING

An introduction to Q-Learning with a practical Python example
Nicolo Cosimo Albanese
Aug 25
Editors' Picks
The Next Step is Responsible AI. How Do We Get There?
THE NEXT STEP IS RESPONSIBLE AI. HOW DO WE GET THERE?

Machine learning solutions take an important place in our lives. It is not only
about performance anymore but also about responsibility.
Erdogan Taskesen
Aug 26
Legal and Ethical Perspectives on Generative AI
LEGAL AND ETHICAL PERSPECTIVES ON GENERATIVE AI

Exploring the implications of AI-generated content from the legal and
ethical aspects
Olivia Tanuwidjaja
Aug 25
RAG vs Finetuning — Which Is the Best Tool to Boost Your LLM Application?
RAG VS FINETUNING — WHICH IS THE BEST TOOL TO BOOST YOUR LLM APPLICATION?

The definitive guide for choosing the right method for your use case
Heiko Hotz
Aug 24
Archetypes of the Data Scientist Role
ARCHETYPES OF THE DATA SCIENTIST ROLE

Data science roles can be very different, and job postings are not always clear.
What hat do you want to wear?
Stephanie Kirmer
Aug 23
Topic Modeling with Llama 2
TOPIC MODELING WITH LLAMA 2

Create easily interpretable topics with Large Language Models
Maarten Grootendorst
Aug 22
The Future of Music Discovery: Search vs. Generation
THE FUTURE OF MUSIC DISCOVERY: SEARCH VS. GENERATION

Functional music in the age of AI
Max Hilsdorf
Aug 22
Features
Data, Streamlined: How to Build Better Products, Workflows, and Teams
DATA, STREAMLINED: HOW TO BUILD BETTER PRODUCTS, WORKFLOWS, AND TEAMS

Our weekly selection of must-read Editors’ Picks and original features
TDS Editors
Aug 24
Learning New Data Science Skills, The Right Way
LEARNING NEW DATA SCIENCE SKILLS, THE RIGHT WAY

Our weekly selection of must-read Editors’ Picks and original features
TDS Editors
Aug 17
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Deep Dives
Beyond Bar Charts: Data with Sankey, Circular Packing, and Network Graphs
BEYOND BAR CHARTS: DATA WITH SANKEY, CIRCULAR PACKING, AND NETWORK GRAPHS

Unconventional visualizations: when and when not to wield their power
Maham Haroon
Aug 26
Monte Carlo Approximation Methods: Which one should you choose and when?
MONTE CARLO APPROXIMATION METHODS: WHICH ONE SHOULD YOU CHOOSE AND WHEN?

Is it Inverse Transformation, Random Walk Metropolis-Hastings, or Gibbs? An
analysis focusing on the mathematical foundation, Python…
Suyang Li
Aug 25
Discovering the Maxflow Mincut Theorem: A Comprehensive and Formal Approach
DISCOVERING THE MAXFLOW MINCUT THEOREM: A COMPREHENSIVE AND FORMAL APPROACH

Exploring the field of flow networks and the Maxflow Mincut theorem
Daniel García Solla
Aug 24
Comparing and Explaining Diffusion Models in HuggingFace Diffusers
COMPARING AND EXPLAINING DIFFUSION MODELS IN HUGGINGFACE DIFFUSERS

DDPM, Stable Diffusion, DALL·E-2, Imagen, Kandinsky 2, SDEdit, ControlNet,
InstructPix2Pix, and more
Mario Namtao Shianti Larcher
Aug 24
Great Applied (Data) Science Work
GREAT APPLIED (DATA) SCIENCE WORK

What helps solve real-life problems end-to-end, from business requirements to
convincing presentation of results
Lars Roemheld
Aug 23
Program-Aided Language Models
PROGRAM-AIDED LANGUAGE MODELS

LLMs can write code, but what if they can execute programs?
Cameron R. Wolfe, Ph.D.
Aug 23
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