Machine Learning
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Machine learning insights, practical tutorials, and clear explanations for beginners and aspiring data scientists. Follow the channel for models, algorithms, coding guides, and real-world ML applications.
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Machine Learning
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Machine Learning
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Model Calibration, Explained: A Visual Guide with Code Examples for Beginners
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Category:
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Date: 2025-01-10 |
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Read time: 14 min read
When all models have similar accuracy, now what?
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Sustainable Business Strategy with Data Analytics
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Category: DATA SCIENCE
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Date: 2025-01-10 |
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Read time: 13 min read
Use data analytics to help companies design and implement strategic sustainability roadmaps to reduce theirβ¦
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Linearizing Llama
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Category: LARGE LANGUAGE MODELS
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Date: 2025-01-10 |
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Read time: 12 min read
Speeding Up Llama: A Hybrid Approach to Attention Mechanisms
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Mastering Transparent Images: Adding a Background Layer
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Category: DATA SCIENCE
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Date: 2025-01-10 |
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Read time: 6 min read
How to Process Images with an Alpha Channel using OpenCV + Python
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What to Do If the Logit Decision Boundary Fails?
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Category: MACHINE LEARNING
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Date: 2025-01-09 |
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Read time: 6 min read
Feature engineering for classification models using Bayesian Machine Learning
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How to Run Jupyter Notebooks and Generate HTML Reports with Python Scripts
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Category: DATA SCIENCE
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Date: 2025-01-09 |
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Read time: 13 min read
A step-by-step guide to automating Jupyter Notebook execution and report generation using Python
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Data-Driven Decision Making with Sentiment Analysis in R
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Category: NATURAL LANGUAGE PROCESSING
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Date: 2025-01-21 |
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Read time: 15 min read
Leveraging the Quanteda, Textstem and Sentimentr Packages to Extract Customer Insights and Enhance Business Strategy
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Understanding the Evolution of ChatGPT: Part 3- Insights from Codex and InstructGPT
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Category: CHATGPT
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Date: 2025-01-21 |
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Read time: 22 min read
Mastering the art of fine-tuning: Learnings for training your own LLMs.
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Learn to Build Advanced AI Image Applications
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Category: DATA SCIENCE
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Date: 2025-01-21 |
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Read time: 25 min read
By building an interior designer in ComfyUI
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Skills a Data Scientist Must Have (But a Software Engineer Doesnβt)
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Category: CAREER ADVICE
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Date: 2025-01-21 |
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Read time: 11 min read
I guided a friend through her career transition to being an ML engineer.
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Machine Learning
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Build your own Annotation Tool for Image Classification in 5 Minutes
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Category: DATA SCIENCE
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Date: 2025-01-21 |
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Read time: 5 min read
How to label an image dataset with OpenCV and Python
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Urban Graph Networks
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Category: DATA SCIENCE
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Date: 2025-01-21 |
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Read time: 14 min read
How graph theory can save you hours for your next city trip!
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Building a Data Dashboard
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Category: DATA SCIENCE
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Date: 2025-01-20 |
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Read time: 15 min read
Using the streamlit Python library
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Why Generative-AI Appsβ Quality Often Sucks and What to Do About It
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Category:
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Date: 2025-01-20 |
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Read time: 23 min read
How to get from PoCs to tested high-quality applications in production
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How Most Organizations Get Data Strategy Wrong β and How to Fix It
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Category: ARTIFICIAL INTELLIGENCE
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Date: 2025-01-20 |
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Read time: 79 min read
Redefining Data Strategy to Drive Competitive Advantage with Data, Analytics and AI
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RAG Isnβt Immune to LLM Hallucination
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Category: ARTIFICIAL INTELLIGENCE
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Date: 2025-01-20 |
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Read time: 11 min read
How to measure how much of your RAGβs output is correct
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Statistical Learnability of Strategic Linear Classifiers: A Proof Walkthrough
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Category: MACHINE LEARNING
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Date: 2025-01-08 |
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Read time: 19 min read
With the help of an intricate geometric construction, we can prove that instance-wise cost functionsβ¦
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Linear Programming: Auxiliary Variables
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Category: DATA SCIENCE
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Date: 2025-01-08 |
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Read time: 15 min read
Part 5: Increasing LP flexibility to handle tricky logic
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Building Effective Metrics to Describe Users
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Category: ANALYTICS
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Date: 2025-01-08 |
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Read time: 4 min read
How can numerical user metrics be transformed into a personalized assessment of whether this behaviorβ¦
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Customizing Your Fine-tuning Code Using HuggingFaceβs Transformers Library
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Date: 2025-01-08 |
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Read time: 8 min read
Examples of custom callbacks and custom fine-tuning code from different libraries
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