Back to Basics: Databases, SQL, and Other Data-Processing Must-Reads
Our weekly selection of must-read Editors' Picks and original features- 28777Murphy2025-03-22
A Proposed Perfect Package Prototype for Python Projects
How to structure your Python package projects to ensure efficiency, effectiveness and future-proofing- 27057Murphy2025-03-22
Should You Join FAANG or a Startup as a Data Scientist?
Lessons from working at Uber + Meta, a growth stage company and a tiny startup- 29672Murphy2025-03-22
PySpark Explained: The explode and collect_list Functions
Two useful functions to nest and un-nest data sets in PySpark- 22128Murphy2025-03-22
Statistically Confirm Your -Comparing Pandas and Polars with 1 Million Rows of Data
Using the Independent samples t-test and Welch's t-test to compare scores in benchmarking.- 27495Murphy2025-03-22
Why You (Currently) Do Not Need Deep Learning for Time Series Forecasting
What you need instead: Learnings from the Makridakis M5 competitions and the 2023 Kaggle AI report- 26522Murphy2025-03-22
Chart Wars – Stacked Bar Chart vs. Heatmap
The winner is obvious- 22297Murphy2025-03-22
Using Power BI for Planning (Warehouse) with Stock Values
How can we use Power BI to plan for the future using Stock-Measures? Here, I show you a possible approach.- 27883Murphy2025-03-22
How Do Computers Actually Remember?
A Budding Data Scientist's Introduction to Computer Hardware- 23379Murphy2025-03-22
Get started with SQLite3 in Python Creating Tables & Fetching Rows
Learn to use SQLite - The most used DBMS in the world- 28821Murphy2025-03-22
Let's Revisit Case-When in Different Libraries Including the New Player: Pandas
How to create conditional columns with different tools.- 26482Murphy2025-03-22
Creating an Assistant with OpenAI Assistant API and Streamlit
A step-by-step guide- 28462Murphy2025-03-22
How to Find and Solve Valuable Generative AI Use Cases
80% of AI projects fail due to poor use cases or technical knowledge. Gen AI reduced complexity, and now we must pick the right battles.- 29288Murphy2025-03-22
3 Simple Statistical Methods for Outlier Detection
If it works, keep it simple- 24704Murphy2025-03-22
Nailing the Machine Learning Design Interview
Tips and tricks for FAANG design interviews- 27720Murphy2025-03-22
Incorporate an LLM Chatbot into Your Web Application with OpenAI, Python, and Shiny
Step-by-Step Integration of AI Chatbots into Shiny for Python Applications: From API Setup to User Interaction.- 20995Murphy2025-03-22
CLIP, LLaVA, and the Brain
What neuroscience can teach us about the limitations of modern multimodal transformers- 27571Murphy2025-03-22
How I Created a Kaggle-Like Platform for My Students Using Streamlit and How You Can Do It as Well
Gamify machine learning student projects with Streamlit and Google Sheets- 24228Murphy2025-03-22
Understanding Techniques for Solving GenAI Challenges
Dive into model pre-training, fine-tuning, RAG, prompt engineering, and more!- 27906Murphy2025-03-22
Counts Outlier Detector: Interpretable Outlier Detection
An interpretable outlier detector based on multi-dimensional histograms.- 22028Murphy2025-03-22
The current state of continual learning in AI
Why is ChatGPT only trained up until 2021?Optimizing Pandas Code: The Impact of Operation Sequence
Learn how to rearrange your code to achieve significant speed improvements.