Author

R_Talks

@rccareers3004

articles: 16
total claps: 133
top claps: 94
avg read: 8.0 min
active: 2026-05-14 → 2026-06-17

Wiki topics

ML · Machine Learning · 16 🔬 · Science · General · 16 EDU · Education & Learning · 13 OPS · LLMOps & Inference · 3 📐 · Mathematics · 3 AIM · AI in Marketing · 2 GRW · Growth & Analytics · 2 💻 · Programming · 1

Top tags

#data-science ·16 #machine-learning ·12 #statistical-analysis ·3 #causal-inference ·3 #timeseries ·2 #martech ·2 #hypothesis-testing ·1 #ab-testing ·1 #pca-analysis ·1 #data-visualization ·1

HUM AI SCI

RT R_Talks

A Practical Guide to Confidence Intervals, Prediction Intervals, and Model Accuracy: Understanding…

“It is better to be roughly right than precisely wrong.” — John Maynard Keynes

May 21, 2026 · 7 min read · 94 claps #data-science #machine-learning #confidence-interval

A Practical Guide to Confidence Intervals, Prediction Intervals, and Model Accuracy: Understanding…

HUM AI SCI

RT R_Talks

Transformers 101: A Data Scientist’s Guide to Self-Attention, Sequence Modeling, and Production…

“For decades, computers processed language like an assembly line — one slow, sequential step at a time. The Transformer changed the world…

Jun 03, 2026 · 9 min read · 31 claps #data-science #machine-learning #deep-learning

Transformers 101: A Data Scientist’s Guide to Self-Attention, Sequence Modeling, and Production…

MED SOC AI SCI

RT R_Talks

Simpson’s Paradox: The Statistical Illusion That Has Fooled Doctors, Courts, and Data Scientists

“The first principle is that you must not fool yourself — and you are the easiest person to fool.” — Richard Feynman

May 14, 2026 · 7 min read · 3 claps #data-science #causal-inference #causal-data-science

Simpson’s Paradox: The Statistical Illusion That Has Fooled Doctors, Courts, and Data Scientists

AI SCI DSN

RT R_Talks

A Practical Guide to PCA: How to Shrink Your Data Without Losing What Matters

“The art of being wise is the art of knowing what to overlook.” — William James

May 15, 2026 · 6 min read · 3 claps #data-science #pca-analysis #statistical-analysis

A Practical Guide to PCA: How to Shrink Your Data Without Losing What Matters

HUM MDA AI TCH SCI

RT R_Talks

Sliding Windows in Time Series: A Data Scientist’s Guide to Feature Engineering, Validation, and…

“Static machine learning models see the world as a single snapshot. Time-series models with sliding windows see the world as a movie —…

Jun 17, 2026 · 10 min read · 1 claps #data-science #machine-learning #feature-engineering

Sliding Windows in Time Series: A Data Scientist’s Guide to Feature Engineering, Validation, and…

HUM AI SCI

RT R_Talks

CausalML 101: A Beginner’s Guide to Uplift Modeling and Causal Inference in Python

“The goal of machine learning is to predict what will happen. The goal of causal inference is to make something happen.”

May 29, 2026 · 9 min read · 1 claps #data-science #machine-learning #causal-inference

CausalML 101: A Beginner’s Guide to Uplift Modeling and Causal Inference in Python

HUM AI SCI

RT R_Talks

Unmasking the Mathematics: The 5 Most Misunderstood Concepts in Regression Models

“All models are wrong, but some are useful.” — George Box

Jun 12, 2026 · 12 min read · 0 claps #data-science #machine-learning #linear-regression

Unmasking the Mathematics: The 5 Most Misunderstood Concepts in Regression Models

MKT HUM AI SCI

RT R_Talks

RFM Analysis 101: A Data Scientist’s Guide to Customer Segmentation, Predictive Lifetime Value, and…

“Standard machine learning seeks to predict what a customer will do next. RFM analysis is the mathematical framework that groups them by…

Jun 13, 2026 · 11 min read · 0 claps #data-science #rfm-analysis #machine-learning

RFM Analysis 101: A Data Scientist’s Guide to Customer Segmentation, Predictive Lifetime Value, and…

HUM AI SCI

RT R_Talks

Computer Vision 101: A Data Scientist’s Guide to Image Representation, Deep Feature Extraction, and…

“A computer does not see a landscape, a face, or a self-driving lane. It sees an infinite grid of integers. Computer Vision is the…

Jun 09, 2026 · 10 min read · 0 claps #data-science #computer-vision #machine-learning

Computer Vision 101: A Data Scientist’s Guide to Image Representation, Deep Feature Extraction, and…

HUM LIF AI SCI

RT R_Talks

The ARIMA Family 101: A Data Scientist’s Guide to Autoregressive Sequence Modeling and Production…

“To understand where you are going, you must first understand where you have been. In the ARIMA family, the past is not just context — it…

Jun 07, 2026 · 9 min read · 0 claps #data-science #timeseries #arima-model

The ARIMA Family 101: A Data Scientist’s Guide to Autoregressive Sequence Modeling and Production…

AI SCI

RT R_Talks

A Practical Guide to A/B/n Testing: When One Challenger Is Not Enough

“Do not put all your eggs in one basket.” — Miguel de Cervantes

May 17, 2026 · 7 min read · 0 claps #data-science #statistical-analysis #hypothesis-testing

A Practical Guide to A/B/n Testing: When One Challenger Is Not Enough

HUM GEN AI SCI

RT R_Talks

A Beginner’s Guide to Machine Learning on Graphs: From Node Embeddings to Graph Neural Networks

“The strength of the team is each individual member. The strength of each member is the team.” — Phil Jackson

May 23, 2026 · 7 min read · 0 claps #data-science #machine-learning #gnn

A Beginner’s Guide to Machine Learning on Graphs: From Node Embeddings to Graph Neural Networks

HUM AI SCI

RT R_Talks

A Practical Guide to Generalized Linear Models: When Linear Regression Is Not Enough

“All models are wrong, but some are useful.” — George Box

May 20, 2026 · 6 min read · 0 claps #data-science #machine-learning #generalized-linear-model

A Practical Guide to Generalized Linear Models: When Linear Regression Is Not Enough

MKT HUM AI SCI

RT R_Talks

A Practical Guide to Customer Lifetime Value: The Metric That Changes How You Think About Every…

“Not all customers are created equal — but most businesses treat them as if they are.”

May 16, 2026 · 6 min read · 0 claps #data-science #customer-lifetime-value #martech

A Practical Guide to Customer Lifetime Value: The Metric That Changes How You Think About Every…

HUM AI SCI

RT R_Talks

Causal Inference 101: A Data Scientist’s Guide to Moving Beyond Correlation

Standard machine learning finds correlations to predict outcomes. Causal inference discovers the interventions that change them.

May 28, 2026 · 6 min read · 0 claps #data-science #causal-inference #propensity-model

Causal Inference 101: A Data Scientist’s Guide to Moving Beyond Correlation

TCH HUM AI SCI

RT R_Talks

A Beginner’s Practical Guide to ML Pipelines: How to Build Models That Are Reproducible, Reliable…

“Give me six hours to chop down a tree and I will spend the first four sharpening the axe.” — Abraham Lincoln

May 28, 2026 · 6 min read · 0 claps #data-science #data-pipeline #machine-learning