DeepGuide for DeepSeek

The Power of Pandas Plots: Backends
Create interactive graphics from Pandas effortlessly
25548Murphy2025-03-23
Using Generative AI To Get Insights From Disorderly Data
Best practices for using Large Language Models to extract actionable insights even with poor metadata
25263Murphy2025-03-23
The Ultimate Guide to Vision Transformers
A comprehensive guide to the Vision Transformer (ViT) that revolutionized computer vision.
24124Murphy2025-03-23
Hands On Neural Networks and Time Series, with Python
From the very simple Feed Forward Neural Networks to the majestic transformers: everything you need to know
22937Murphy2025-03-23
Essential Guide to Continuous Ranked Probability Score (CRPS) for Forecasting
Learn how to evaluate probabilistic forecasts and how CRPS relates to other metrics
24828Murphy2025-03-23
A Comprehensive Introduction to Marketing Data Engineering
Fundamentals, responsibilities, and challenges
25935Murphy2025-03-23
How to Deal with Time Series Outliers
Understanding, detecting and replacing outliers in time series
21198Murphy2025-03-23
A Simple Framework for RAG Enhanced Visual Question Answering
Empowering Phi-3.5-vision with Wikipedia knowledge for augmented Visual Question Answering.
22068Murphy2025-03-23
Data Scientists Can't Excel in Python Without Mastering These Functions
Introduction of Python's core functions, use cases, scripts, and underlying mechanisms
27276Murphy2025-03-23
Streamline Property Data Management: Advanced Data Extraction & Retrieval with Indexify
A Step-by-Step Guide to Document Querying with Indexify
26133Murphy2025-03-23
How to Train a Vision Transformer (ViT) from Scratch
A practical guide to implementing the Vision Transformer (ViT)
25794Murphy2025-03-23
The DIY Path to AI Product Management: Picking a Starter Project
Building real-world skills through hands-on trial and error.
25640Murphy2025-03-23
Hands-On Global Optimization Methods, with Python
Four methods to find the maximum (or minimum) of your black box objective function
25305Murphy2025-03-23
Here Comes Mamba: The Selective State Space Model
Part 3 - Towards Mamba State Space Models for Images, Videos and Time Series
25506Murphy2025-03-23
Building Scalable Data Platforms
Data Mesh trends in data platform design
25839Murphy2025-03-23
Diving Deeper with Structured Outputs
Enhancing our understanding and optimal usage of structured outputs
26712Murphy2025-03-23
Training AI Models on CPU
Revisiting CPU for ML in an Era of GPU Scarcity
26406Murphy2025-03-23
Monte Carlo Methods for Solving Reinforcement Learning Problems
Dissecting "Reinforcement Learning" by Richard S. Sutton with Custom Python Implementations, Episode III
24725Murphy2025-03-23
Create Your Own Meal Planner Using ChatGPT
A brief guide to prompt engineering
24419Murphy2025-03-23
Mathematics of Love: Optimizing a Dining-Room Seating Arrangement for Weddings with Python
Solving the Restricted Quadratic Multi-Knapsack Problem (RQMKP) with mathematical programming and Python
25658Murphy2025-03-23

< 124 125 126 127 128 >

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.

Recommend

◦ The Docker Compose of ETL: Meerschaum Compose

◦ Visualize a business process through data serialization

◦ An Illusion of Life

◦ Efficient Metric Collection in PyTorch: Avoiding the Performance Pitfalls of TorchMetrics

◦ Extracting Information from Natural Language Using Generative AI

◦ A Requiem for the Transformer?

◦ ChatGPT vs. Claude vs. Gemini for Data Analysis (Part 1)

◦ Log Breadcrumbs: only show Logs leading up to an Error

◦ OCR-Free Document Data Extraction with Transformers (2/2)

◦ An Intuitive Guide to Docker for Data Science

◦ Fine-Tuning BERT for Text Classification

◦ Unlocking Growth: 3 Years at Meta - Transformative Lessons for Work and Life