Machine Learning
@DataScienceM
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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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@HusseinSheikho
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Machine Learning
38.9K subscribers
Machine Learning
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I Spent My Money on Benchmarking LLMs on Dutch Exams So You Donβt Have To
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Category: LARGE LANGUAGE MODELS
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Date: 2024-09-25 |
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Read time: 12 min read
OpenAIβs new o1-preview is way too expensive for how it performs on the results
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How Cohort Analysis Can Transform Your Customer Insights
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Category:
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Date: 2024-09-25 |
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Read time: 6 min read
Discover how tracking customer behavior over time with cohort analysis can improve engagement and retentionβ¦
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Exposing Jailbreak Vulnerabilities in LLM Applications with ARTKIT
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Category: MACHINE LEARNING
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Date: 2024-09-25 |
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Read time: 10 min read
Automated prompt-based testing to extract hidden passwords in the popular Gandalf challenge
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Convenient Time Series Forecasting with sktime
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Category: MACHINE LEARNING
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Date: 2024-09-25 |
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Read time: 8 min read
How to make forecasting as easy as a walk in the park
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Water Cooler Small Talk: The Birthday Paradox
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Category: DATA SCIENCE
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Date: 2024-09-25 |
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Read time: 9 min read
A look at the counterintuitive mathematics of shared birthdays
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Doctors Leverage Multimodal Data; Medical AI Should Too
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Category:
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Date: 2024-09-25 |
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Read time: 11 min read
Integrating multimodal data enables a new generation of medical AI systems to better capture doctorβsβ¦
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Iβve hired 3 cohorts of data science interns β hereβs my advice on getting an offer
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Category: DATA SCIENCE
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Date: 2024-09-24 |
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Read time: 16 min read
Resume and interview tips for landing a data science internship
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Feature Engineering Techniques for Numerical Variables in Python
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Category: MACHINE LEARNING
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Date: 2024-09-24 |
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Read time: 21 min read
Learn the most useful feature engineering techniques to convert numerical values ββinto useful information forβ¦
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Building an Interactive UI for Llamaindex Workflows
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Category:
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Date: 2024-09-24 |
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Read time: 11 min read
A guide to integrating human-in-the-loop interactions using Llamaindex, FastAPI, and Streamlit
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A Deep Dive into Odds Ratio
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Category: STATISTICS
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Date: 2024-09-24 |
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Read time: 20 min read
Understanding, calculating, visualizing, and interpreting odds ratios and their confidence intervals with practical examples inβ¦
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Zero-Shot Localization with CLIP-Style Encoders
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Category: ARTIFICIAL INTELLIGENCE
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Date: 2024-09-24 |
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Read time: 11 min read
How can we see what a vision encoder sees?
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Semantic Layer for the People and by the People
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Category:
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Date: 2024-09-23 |
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Read time: 14 min read
My 3 +1 jokers with templates for building a powerful analytical semantic layer
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Graph RAG into Production β step-by-step
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Category: ARTIFICIAL INTELLIGENCE
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Date: 2024-09-23 |
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Read time: 17 min read
A GCP native, fully serverless implementation that you will replicate in minutes
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Breaking It Down : Chunking Techniques for Better RAG
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Category:
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Date: 2024-09-23 |
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Read time: 19 min read
Mastering chunking for efficient retrieval in RAG systems
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Programming an Arduino with CrewAI Agents
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Category: PROGRAMMING
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Date: 2024-09-23 |
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Read time: 7 min read
An interaction between electronics and LLMs
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Embeddings Are Kind of Shallow
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Category: LARGE LANGUAGE MODELS
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Date: 2024-09-23 |
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Read time: 33 min read
What I learned doing semantic search on U.S. Presidents with four language model embeddings
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Build Your Agents from Scratch
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Category:
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Date: 2024-09-23 |
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Read time: 8 min read
Design your own agents without any framework
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Data Empowers Business
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Category: DATA ENGINEERING
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Date: 2024-09-22 |
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Read time: 10 min read
Exploiting the full potential of universal data supply
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How I Deal with Hallucinations at an AI Startup
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Category: ARTIFICIAL INTELLIGENCE
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Date: 2024-09-22 |
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Read time: 8 min read
And the difference between weak vs strong grounding
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Hands-On Numerical Derivative with Python, from Zero to Hero
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Category: DATA SCIENCE
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Date: 2024-09-22 |
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Read time: 10 min read
Hereβs everything you need to know (beyond the standard definition) to master the numerical derivativeβ¦
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