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Why Data Science May Not Be For You
Why Data Science May Not Be For You
Tell-tale signs why a career in data science may not suit you
Egor Howell
May 4
Enhance Your Network with the Power of a Graph DB
Enhance Your Network with the Power of a Graph DB
Get yourself set up in 5 mins with a graph DB and an interactive visualization, with all the code to do it written for you.
Benjamin Lee
May 4
Latest
Dissolving map boundaries in QGIS and Python
Dissolving map boundaries in QGIS and Python
This post describes some interesting processes for transforming the map boundaries in vector datasets using QGIS and geopandas in Python.
Himalaya Bir Shrestha
May 4
Why and When to Use the Generalized Method of Moments
Why and When to Use the Generalized Method of Moments
It’s a highly flexible estimation technique that can be applied in a variety of situations
Luis Felipe de Souza Rodrigues
May 3
Deep Dive into LlaMA 3 by Hand ✍️
Deep Dive into LlaMA 3 by Hand ✍️
Explore the nuances of the transformer architecture behind Llama 3 and its prospects for the GenAI ecosystem
Srijanie Dey, PhD
May 3
On Handling Precalculated Hierarchical Data in Power BI
On Handling Precalculated Hierarchical Data in Power BI
While hierarchies are a familiar concept with data, some sources deliver their data in an unusual format. Let’s see a not-so-unusual case.
Salvatore Cagliari
May 3
Turn Llama 3 into an Embedding Model with LLM2Vec
Turn Llama 3 into an Embedding Model with LLM2Vec
RAG with Llama 3 for the generation and the retrieval
Benjamin Marie
May 3
Cyclical Encoding: An Alternative to One-Hot Encoding for Time Series Features
Cyclical Encoding: An Alternative to One-Hot Encoding for Time Series Features
Cyclical encoding provides your model with the same information using significantly fewer features
Haden P
May 3
Courage to Learn ML: Tackling Vanishing and Exploding Gradients (Part 2)
Courage to Learn ML: Tackling Vanishing and Exploding Gradients (Part 2)
A Comprehensive Survey on Activation Functions, Weights Initialization, Batch Normalization, and Their Applications in PyTorch
Amy Ma
May 3
Demystifying Shiny Modules by Transforming a Bigfoot Sightings App Modular
Demystifying Shiny Modules by Transforming a Bigfoot Sightings App Modular
In-depth guide to learning how to build Shiny applications using modules.
Deepsha Menghani
May 3
Modeling Slowly Changing Dimensions
Modeling Slowly Changing Dimensions
A deep dive into the various SCD types and how they can be implemented in Data Warehouses
Giorgos Myrianthous
May 3
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