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scipio
@scipio
67
Does it matter who's right, or who's left?
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October 24, 2017
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scipio
blog
2026-04-03 11:00
Learn Zig Series (#9) - Comptime (Zig's Superpower)
Learn Zig Series (#9) - Comptime (Zig's Superpower) What will I learn You will learn what compile-time execution (comptime) is and why it matters; comptime variables and inline for loops that unroll at
$ 0.700
8
scipio
StemSocial
2026-04-03 07:23
Learn AI Series (#24) - Dimensionality Reduction - PCA
Learn AI Series (#24) - Dimensionality Reduction - PCA What will I learn You will learn the curse of dimensionality -- why more features isn't always better, and how high-dimensional spaces break your
$ 0.431
10
scipio
StemSocial
2026-04-02 18:33
Learn AI Series (#23) - Advanced Clustering - Beyond K-Means
Learn AI Series (#23) - Advanced Clustering - Beyond K-Means What will I learn You will learn DBSCAN -- density-based clustering that finds arbitrarily shaped clusters and identifies noise points
$ 1.042
20
scipio
blog
2026-04-02 11:08
Learn Zig Series (#8) - Pointers and Memory Layout
Learn Zig Series (#8) - Pointers and Memory Layout What will I learn You will learn how single-item pointers (*T) work in Zig; the difference between *T (mutable pointer) and *const T (read-only pointer);
$ 0.986
10
scipio
StemSocial
2026-04-02 07:47
Learn AI Series (#22) - K-Means Clustering - Finding Groups
Learn AI Series (#22) - K-Means Clustering - Finding Groups What will I learn You will learn unsupervised learning -- discovering structure in data without any labels at all; the K-Means algorithm from
$ 0.904
19
scipio
StemSocial
2026-04-01 18:59
Learn AI Series (#21) - Mini Project - Predicting Crypto Market Regimes
Learn AI Series (#21) - Mini Project - Predicting Crypto Market Regimes What will I learn You will learn how to apply everything from episodes #1-20 to a real, messy, end-to-end classification problem;
$ 2.338
404
1
scipio
blog
2026-04-01 10:50
Learn Zig Series (#7) - Memory Management and Allocators
Learn Zig Series (#7) - Memory Management and Allocators What will I learn You will learn the fundamental difference between stack and heap memory; why Zig makes every allocation explicit (no hidden malloc,
$ 1.028
16
1
scipio
StemSocial
2026-04-01 07:52
Learn AI Series (#20) - Support Vector Machines - Drawing the Perfect Boundary
Learn AI Series (#20) - Support Vector Machines - Drawing the Perfect Boundary What will I learn You will learn the maximum margin principle -- why SVMs seek the widest possible gap between classes, and
$ 1.271
14
scipio
StemSocial
2026-03-31 19:07
Learn AI Series (#19) - Gradient Boosting - The Kaggle Champion
Learn AI Series (#19) - Gradient Boosting - The Kaggle Champion What will I learn You will learn the difference between bagging and boosting -- two fundamentally different ensemble strategies that start
$ 2.231
520
scipio
blog
2026-03-31 10:51
Learn Zig Series (#6) - Structs, Enums, and Tagged Unions
Learn Zig Series (#6) - Structs, Enums, and Tagged Unions What will I learn You will learn how to define structs with fields, default values, and methods; the difference between value methods and pointer
$ 1.094
11
scipio
StemSocial
2026-03-31 07:48
Learn AI Series (#18) - Random Forests - Wisdom of Crowds
Learn AI Series (#18) - Random Forests - Wisdom of Crowds What will I learn You will learn why combining many weak models creates a strong one -- the ensemble principle and the math that makes it work;
$ 1.586
15
scipio
StemSocial
2026-03-30 19:44
Learn AI Series (#17) - Decision Trees - How Machines Make Decisions
Learn AI Series (#17) - Decision Trees - How Machines Make Decisions What will I learn You will learn how decision trees split data by asking yes/no questions about features -- a radically different approach
$ 2.209
415
1
scipio
blog
2026-03-30 11:47
Learn Zig Series (#5) - Arrays, Slices, and Strings
Learn Zig Series (#5) - Arrays, Slices, and Strings What will I learn You will learn about arrays in Zig -- fixed size, stack-allocated, compile-time known; slices as pointer-plus-length views into memory;
$ 0.995
8
scipio
StemSocial
2026-03-30 08:55
Learn AI Series (#16) - Scikit-Learn - The Standard Library of ML
Learn AI Series (#16) - Scikit-Learn - The Standard Library of ML What will I learn You will learn why scikit-learn became the standard ML library and how its API design makes everything we built from
$ 1.418
25
scipio
StemSocial
2026-03-29 19:18
Learn AI Series (#15) - Feature Engineering and Selection
Learn AI Series (#15) - Feature Engineering and Selection What will I learn You will learn how to create new features from raw data that help your model find patterns it couldn't see before; interaction
$ 1.226
21
scipio
blog
2026-03-29 11:30
Learn Zig Series (#4) - Error Handling (Zig's Best Feature)
Learn Zig Series (#4) - Error Handling (Zig's Best Feature) What will I learn You will learn why most languages get error handling wrong and how Zig fixes it; error unions -- the ! operator that connects
$ 1.148
16
scipio
StemSocial
2026-03-29 08:33
Learn AI Series (#14) - Data Preparation - The 80% Nobody Talks About
Learn AI Series (#14) - Data Preparation - The 80% Nobody Talks About What will I learn You will learn the three-way split (train/validation/test) and why two sets are not enough for serious ML work; the
$ 1.315
27
scipio
StemSocial
2026-03-28 19:19
Learn AI Series (#13) - Evaluation - How to Know If Your Model Actually Works
Learn AI Series (#13) - Evaluation - How to Know If Your Model Actually Works What will I learn You will learn why accuracy alone is a terrible metric for most real-world problems; the confusion matrix
$ 2.664
641
1
scipio
blog
2026-03-28 11:59
Learn Zig Series (#3) - Functions and Control Flow
Learn Zig Series (#3) - Functions and Control Flow What will I learn You will learn how to define and call functions in Zig with explicit parameter types and return types; how Zig handles multiple return
$ 1.165
13
scipio
StemSocial
2026-03-28 08:50
Learn AI Series (#12) - Classification - Logistic Regression From Scratch
Learn AI Series (#12) - Classification - Logistic Regression From Scratch What will I learn You will learn the difference between regression and classification -- predicting categories, not numbers; the
$ 0.950
16