📌 The Machine Learning “Advent Calendar” Day 21: Gradient Boosted Decision Tree Regressor in Excel
🗂 Category: MACHINE LEARNING
🕒 Date: 2025-12-22 | ⏱️ Read time: 10 min read
Gradient descent in function space with decision trees
#DataScience #AI #Python
🗂 Category: MACHINE LEARNING
🕒 Date: 2025-12-22 | ⏱️ Read time: 10 min read
Gradient descent in function space with decision trees
#DataScience #AI #Python
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📌 The Machine Learning “Advent Calendar” Day 20: Gradient Boosted Linear Regression in Excel
🗂 Category: MACHINE LEARNING
🕒 Date: 2025-12-22 | ⏱️ Read time: 10 min read
From Random Ensembles to Optimization: Gradient Boosting Explained
#DataScience #AI #Python
🗂 Category: MACHINE LEARNING
🕒 Date: 2025-12-22 | ⏱️ Read time: 10 min read
From Random Ensembles to Optimization: Gradient Boosting Explained
#DataScience #AI #Python
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📌 ChatLLM Presents a Streamlined Solution to Addressing the Real Bottleneck in AI
🗂 Category: SPONSORED CONTENT
🕒 Date: 2025-12-22 | ⏱️ Read time: 8 min read
For the last couple of years, a lot of the conversation around AI has revolved…
#DataScience #AI #Python
🗂 Category: SPONSORED CONTENT
🕒 Date: 2025-12-22 | ⏱️ Read time: 8 min read
For the last couple of years, a lot of the conversation around AI has revolved…
#DataScience #AI #Python
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📌 The Machine Learning “Advent Calendar” Day 23: CNN in Excel
🗂 Category: MACHINE LEARNING
🕒 Date: 2025-12-23 | ⏱️ Read time: 8 min read
A step-by-step 1D CNN for text, built in Excel, where every filter, weight, and decision…
#DataScience #AI #Python
🗂 Category: MACHINE LEARNING
🕒 Date: 2025-12-23 | ⏱️ Read time: 8 min read
A step-by-step 1D CNN for text, built in Excel, where every filter, weight, and decision…
#DataScience #AI #Python
📌 How Agents Plan Tasks with To-Do Lists
🗂 Category: AGENTIC AI
🕒 Date: 2025-12-23 | ⏱️ Read time: 7 min read
Understanding the process behind agentic planning and task management in LangChain
#DataScience #AI #Python
🗂 Category: AGENTIC AI
🕒 Date: 2025-12-23 | ⏱️ Read time: 7 min read
Understanding the process behind agentic planning and task management in LangChain
#DataScience #AI #Python
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📌 Stop Retraining Blindly: Use PSI to Build a Smarter Monitoring Pipeline
🗂 Category: MACHINE LEARNING
🕒 Date: 2025-12-23 | ⏱️ Read time: 6 min read
A data scientist’s guide to population stability index (PSI)
#DataScience #AI #Python
🗂 Category: MACHINE LEARNING
🕒 Date: 2025-12-23 | ⏱️ Read time: 6 min read
A data scientist’s guide to population stability index (PSI)
#DataScience #AI #Python
📌 The Machine Learning “Advent Calendar” Day 24: Transformers for Text in Excel
🗂 Category: MACHINE LEARNING
🕒 Date: 2025-12-24 | ⏱️ Read time: 10 min read
An intuitive, step-by-step look at how Transformers use self-attention to turn static word embeddings into…
#DataScience #AI #Python
🗂 Category: MACHINE LEARNING
🕒 Date: 2025-12-24 | ⏱️ Read time: 10 min read
An intuitive, step-by-step look at how Transformers use self-attention to turn static word embeddings into…
#DataScience #AI #Python
📌 Is Your Model Time-Blind? The Case for Cyclical Feature Encoding
🗂 Category: DATA SCIENCE
🕒 Date: 2025-12-24 | ⏱️ Read time: 7 min read
How cyclical encoding improves machine learning prediction
#DataScience #AI #Python
🗂 Category: DATA SCIENCE
🕒 Date: 2025-12-24 | ⏱️ Read time: 7 min read
How cyclical encoding improves machine learning prediction
#DataScience #AI #Python
📌 4 Techniques to Optimize AI Coding Efficiency
🗂 Category: PROGRAMMING
🕒 Date: 2025-12-24 | ⏱️ Read time: 8 min read
Learn how to code more effectively using AI
#DataScience #AI #Python
🗂 Category: PROGRAMMING
🕒 Date: 2025-12-24 | ⏱️ Read time: 8 min read
Learn how to code more effectively using AI
#DataScience #AI #Python
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📌 Bonferroni vs. Benjamini-Hochberg: Choosing Your P-Value Correction
🗂 Category: STATISTICS
🕒 Date: 2025-12-24 | ⏱️ Read time: 11 min read
Multiple hypothesis testing, P-values, and Monte Carlo
#DataScience #AI #Python
🗂 Category: STATISTICS
🕒 Date: 2025-12-24 | ⏱️ Read time: 11 min read
Multiple hypothesis testing, P-values, and Monte Carlo
#DataScience #AI #Python
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📌 Keeping Probabilities Honest: The Jacobian Adjustment
🗂 Category: DATA SCIENCE
🕒 Date: 2025-12-25 | ⏱️ Read time: 10 min read
An intuitive explanation of transforming random variables correctly.
#DataScience #AI #Python
🗂 Category: DATA SCIENCE
🕒 Date: 2025-12-25 | ⏱️ Read time: 10 min read
An intuitive explanation of transforming random variables correctly.
#DataScience #AI #Python
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📌 Why MAP and MRR Fail for Search Ranking (and What to Use Instead)
🗂 Category: DATA SCIENCE
🕒 Date: 2025-12-25 | ⏱️ Read time: 9 min read
MAP and MRR look intuitive, but they quietly break ranking evaluation. Here’s why these metrics…
#DataScience #AI #Python
🗂 Category: DATA SCIENCE
🕒 Date: 2025-12-25 | ⏱️ Read time: 9 min read
MAP and MRR look intuitive, but they quietly break ranking evaluation. Here’s why these metrics…
#DataScience #AI #Python
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Forwarded from ML Research Hub
ML Engineers: NVIDIA has released a guide for beginners on fine-tuning LLMs using Unsloth.
The guide covers:
- training methods: LoRA, FFT, RL
- when and why to do fine-tuning, real use cases
- how much data and VRAM are required
- how to train locally on DGX Spark, RTX graphics cards, and more
Guide: https://blogs.nvidia.com/blog/rtx-ai-garage-fine-tuning-unsloth-dgx-spark/
👉 https://news.1rj.ru/str/DataScienceT
The guide covers:
- training methods: LoRA, FFT, RL
- when and why to do fine-tuning, real use cases
- how much data and VRAM are required
- how to train locally on DGX Spark, RTX graphics cards, and more
Guide: https://blogs.nvidia.com/blog/rtx-ai-garage-fine-tuning-unsloth-dgx-spark/
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📌 Think Your Python Code Is Slow? Stop Guessing and Start Measuring
🗂 Category: PROGRAMMING
🕒 Date: 2025-12-26 | ⏱️ Read time: 13 min read
A hands-on tour of using cProfile + SnakeViz to find (and fix) the “hot” paths…
#DataScience #AI #Python
🗂 Category: PROGRAMMING
🕒 Date: 2025-12-26 | ⏱️ Read time: 13 min read
A hands-on tour of using cProfile + SnakeViz to find (and fix) the “hot” paths…
#DataScience #AI #Python
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