π I Stole a Wall Street Trick to Solve a Google Trends Data Problem
π Category: DATA SCIENCE
π Date: 2026-03-09 | β±οΈ Read time: 14 min read
A methodology for comparing Google Trends data across countries.
#DataScience #AI #Python
π Category: DATA SCIENCE
π Date: 2026-03-09 | β±οΈ Read time: 14 min read
A methodology for comparing Google Trends data across countries.
#DataScience #AI #Python
β€1
π Building a Like-for-Like solution for Stores in Power BI
π Category: DATA ANALYSIS
π Date: 2026-03-10 | β±οΈ Read time: 10 min read
Like-for-Like (L4L) solutions are essential for comparing elements. Itβs about comparing only comparable elements, inβ¦
#DataScience #AI #Python
π Category: DATA ANALYSIS
π Date: 2026-03-10 | β±οΈ Read time: 10 min read
Like-for-Like (L4L) solutions are essential for comparing elements. Itβs about comparing only comparable elements, inβ¦
#DataScience #AI #Python
π What Are Agent Skills Beyond Claude?
π Category: AGENTIC AI
π Date: 2026-03-10 | β±οΈ Read time: 6 min read
How to design and implement agent skills for custom agents outside the Claude ecosystem
#DataScience #AI #Python
π Category: AGENTIC AI
π Date: 2026-03-10 | β±οΈ Read time: 6 min read
How to design and implement agent skills for custom agents outside the Claude ecosystem
#DataScience #AI #Python
Forwarded from Machine Learning with Python
π A fresh deep learning course from MIT is now publicly available
A full-fledged educational course has been published on the university's website: 24 lectures, practical assignments, homework, and a collection of materials for self-study.
The program includes modern neural network architectures, generative models, transformers, inference, and other key topics.
β‘οΈ Link to the course
tags: #Python #DataScience #DeepLearning #AI
A full-fledged educational course has been published on the university's website: 24 lectures, practical assignments, homework, and a collection of materials for self-study.
The program includes modern neural network architectures, generative models, transformers, inference, and other key topics.
β‘οΈ Link to the course
tags: #Python #DataScience #DeepLearning #AI
β€2
π Hybrid Neuro-Symbolic Fraud Detection: Guiding Neural Networks with Domain Rules
π Category: DEEP LEARNING
π Date: 2026-03-10 | β±οΈ Read time: 14 min read
I really thought I was onto something big: add a couple of simple domain rulesβ¦
#DataScience #AI #Python
π Category: DEEP LEARNING
π Date: 2026-03-10 | β±οΈ Read time: 14 min read
I really thought I was onto something big: add a couple of simple domain rulesβ¦
#DataScience #AI #Python
β€1
π When Data Lies: Finding Optimal Strategies for Penalty Kicks with Game Theory
π Category: DATA SCIENCE
π Date: 2026-03-10 | β±οΈ Read time: 9 min read
A data-driven introduction to game theory, Nash equilibrium, and strategic decision-making
#DataScience #AI #Python
π Category: DATA SCIENCE
π Date: 2026-03-10 | β±οΈ Read time: 9 min read
A data-driven introduction to game theory, Nash equilibrium, and strategic decision-making
#DataScience #AI #Python
Forwarded from Machine Learning with Python
π 23 Years of SPOTO β Claim Your Free IT Certs Prep Kit!
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β°Last Chance β Get It Before Itβs Gone!
π₯Whether you're preparing for #Python, #AI, #Cisco, #PMI, #Fortinet, #AWS, #Azure, #Excel, #comptia, #ITIL, #cloud or any other in-demand certification β SPOTO has got you covered!
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γ»Free Python, Excel, Cyber Security, Cisco, SQL, ITIL, PMP, AWS courses: https://bit.ly/4lk4m3c
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γ»Free AI material and support tools: https://bit.ly/46TpsQ8
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π Join SPOTO 23rd anniversary Lucky Draw:
π± iPhone 17
πfree order
π Amazon Gift Card $50/$100
π AI/CCNA/PMP Course Training + Study Material + eBook
Enter the Draw π: https://bit.ly/3NwkceD
π Become Part of Our IT Learning Circle! resources and support:
https://chat.whatsapp.com/Cnc5M5353oSBo3savBl397
π¬ Want exam help? Chat with an admin now!
wa.link/rozuuw
β°Last Chance β Get It Before Itβs Gone!
π How the Fourier Transform Converts Sound Into Frequencies
π Category: MACHINE LEARNING
π Date: 2026-03-11 | β±οΈ Read time: 26 min read
A visual, intuition-first guide to understanding what the math is really doing β from windingβ¦
#DataScience #AI #Python
π Category: MACHINE LEARNING
π Date: 2026-03-11 | β±οΈ Read time: 26 min read
A visual, intuition-first guide to understanding what the math is really doing β from windingβ¦
#DataScience #AI #Python
β€1
π An Intuitive Guide to MCMC (Part I): The Metropolis-Hastings Algorithm
π Category: MATH
π Date: 2026-03-11 | β±οΈ Read time: 14 min read
Tired of the AI hype? Letβs talk about the probabilistic algorithms actually driving high-end quantitativeβ¦
#DataScience #AI #Python
π Category: MATH
π Date: 2026-03-11 | β±οΈ Read time: 14 min read
Tired of the AI hype? Letβs talk about the probabilistic algorithms actually driving high-end quantitativeβ¦
#DataScience #AI #Python
π Spectral Clustering Explained: How Eigenvectors Reveal Complex Cluster Structures
π Category: MACHINE LEARNING
π Date: 2026-03-11 | β±οΈ Read time: 10 min read
Understanding why spectral clustering outperforms K-means
#DataScience #AI #Python
π Category: MACHINE LEARNING
π Date: 2026-03-11 | β±οΈ Read time: 10 min read
Understanding why spectral clustering outperforms K-means
#DataScience #AI #Python
β€2
π Why Most A/B Tests Are Lying to You
π Category: DATA SCIENCE
π Date: 2026-03-11 | β±οΈ Read time: 14 min read
The 4 statistical sins that invalidate most A/B tests, plus a pre-test checklist and Bayesianβ¦
#DataScience #AI #Python
π Category: DATA SCIENCE
π Date: 2026-03-11 | β±οΈ Read time: 14 min read
The 4 statistical sins that invalidate most A/B tests, plus a pre-test checklist and Bayesianβ¦
#DataScience #AI #Python
π Exploratory Data Analysis for Credit Scoring with Python
π Category: DATA SCIENCE
π Date: 2026-03-12 | β±οΈ Read time: 16 min read
Understanding default risk through statistical analysis of borrower and loan characteristics.
#DataScience #AI #Python
π Category: DATA SCIENCE
π Date: 2026-03-12 | β±οΈ Read time: 16 min read
Understanding default risk through statistical analysis of borrower and loan characteristics.
#DataScience #AI #Python
Forwarded from Machine Learning with Python
Machine Learning in python.pdf
1 MB
Machine Learning in Python (Course Notes)
I just went through an amazing resource on #MachineLearning in #Python by 365 Data Science, and I had to share the key takeaways with you!
Hereβs what youβll learn:
π Linear Regression - The foundation of predictive modeling
π Logistic Regression - Predicting probabilities and classifications
π Clustering (K-Means, Hierarchical) - Making sense of unstructured data
π Overfitting vs. Underfitting - The balancing act every ML engineer must master
π OLS, R-squared, F-test - Key metrics to evaluate your models
https://t.me/CodeProgrammer || Shareπ and Like π
I just went through an amazing resource on #MachineLearning in #Python by 365 Data Science, and I had to share the key takeaways with you!
Hereβs what youβll learn:
π Linear Regression - The foundation of predictive modeling
π Logistic Regression - Predicting probabilities and classifications
π Clustering (K-Means, Hierarchical) - Making sense of unstructured data
π Overfitting vs. Underfitting - The balancing act every ML engineer must master
π OLS, R-squared, F-test - Key metrics to evaluate your models
https://t.me/CodeProgrammer || Share
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Forwarded from Machine Learning with Python
Follow the Machine Learning with Python channel on WhatsApp: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
β€2
π Solving the Human Training Data Problem
π Category: LARGE LANGUAGE MODELS
π Date: 2026-03-12 | β±οΈ Read time: 18 min read
How AI has completely transformed the way I study as a graduate student
#DataScience #AI #Python
π Category: LARGE LANGUAGE MODELS
π Date: 2026-03-12 | β±οΈ Read time: 18 min read
How AI has completely transformed the way I study as a graduate student
#DataScience #AI #Python
π Scaling Vector Search: Comparing Quantization and Matryoshka Embeddings for 80% Cost Reduction
π Category: MACHINE LEARNING
π Date: 2026-03-12 | β±οΈ Read time: 11 min read
Navigating the performance cliff: How pairing MRL with int8 and binary quantization balances infrastructure costsβ¦
#DataScience #AI #Python
π Category: MACHINE LEARNING
π Date: 2026-03-12 | β±οΈ Read time: 11 min read
Navigating the performance cliff: How pairing MRL with int8 and binary quantization balances infrastructure costsβ¦
#DataScience #AI #Python
π I Finally Built My First AI App (And It Wasnβt What I Expected)
π Category: LARGE LANGUAGE MODELS
π Date: 2026-03-12 | β±οΈ Read time: 14 min read
A beginner-friendly walkthrough of API calls, environment variables, and real-world AI infrastructure
#DataScience #AI #Python
π Category: LARGE LANGUAGE MODELS
π Date: 2026-03-12 | β±οΈ Read time: 14 min read
A beginner-friendly walkthrough of API calls, environment variables, and real-world AI infrastructure
#DataScience #AI #Python
β€1
π A Tale of Two Variances: Why NumPy and Pandas Give Different Answers
π Category: DATA SCIENCE
π Date: 2026-03-13 | β±οΈ Read time: 7 min read
Imagine you are analyzing a small dataset: You want to calculate some summary statistics toβ¦
#DataScience #AI #Python
π Category: DATA SCIENCE
π Date: 2026-03-13 | β±οΈ Read time: 7 min read
Imagine you are analyzing a small dataset: You want to calculate some summary statistics toβ¦
#DataScience #AI #Python
π How to Build Agentic RAG with Hybrid Search
π Category: RAG
π Date: 2026-03-13 | β±οΈ Read time: 7 min read
Learn how to build a powerful agentic RAG system
#DataScience #AI #Python
π Category: RAG
π Date: 2026-03-13 | β±οΈ Read time: 7 min read
Learn how to build a powerful agentic RAG system
#DataScience #AI #Python