Comparison

Karnaugh & Boolean Minimizer vs ML_Engineering

Price, ratings, monetisation and update history for both apps, side by side — with what reviewers say about each.

Head to head
About

Karnaugh & Boolean Minimizer

Simplify complex Boolean expressions and Karnaugh maps with step-by-step solutions. This tool supports up to 26 variables and offers multiple minimization algorithms for digital logic design.

Highlights
  • Minimize Karnaugh Maps up to 8 variables
  • Step-by-step Boolean expression simplification
  • Quine–McCluskey algorithm for functions up to 8 variables
  • Multi-Output minimization with Espresso algorithm
  • View minimized solutions in SOP/POS forms
  • Generate circuits from minimized solutions
Features
Currently charting
Read full description

Karnaugh & Boolean Minimizer is an innovative and versatile application for simplifying Karnaugh Maps and Boolean expressions. It is geared for those involved in engineering fields, more precisely electrical engineering students, academics, digital devices constructors or anybody involved with Boolean expressions. With its powerful minimization capabilities and full-fledged features, this tool gives you the flexibility to work with all forms of Boolean expressions and provides quality solutions. Features: - Minimize Karnaugh Maps up to 8 variables - Step-by-step simplification of Boolean expressions up to 26 (A-Z) variables using Boolean algebra laws and theorems - Step-by-step simplification of Boolean functions up to 8 variables by the Quine–McCluskey algorithm, showing the prime implicant chart and using Petrick's method where appropriate - Multi-Output minimization up to 8 inputs and 8 outputs, using the de-facto industry standard Espresso algorithm - View minimized solutions on Karnaugh Map in Sum-of-Product (SOP/CNF) and Product-of-Sum (POS/DNF) forms - Support Don't Cares - Fill Karnaugh map using truth table, sets of terms and Boolean expressions - View all possible solutions for Karnaugh Maps up to 5 variables - Guaranteed minimal solution when using the Karnaugh Map, Quine–McCluskey and Algebraic Minimizer - Highlight minimized term on Karnaugh map - Optimization of minimized solutions with XOR gates - Generate circuit from minimized solution with AND/OR/NAND/NOR logic gates - Generate random Karnaugh Maps, truth tables and Boolean expressions - Custom keyboard for easy input of Boolean expressions - Support all Boolean operators and constants - Fully customizable Karnaugh Map orientation, variable names, operator symbols and expression format - Import/Export Karnaugh Maps and truth tables as CSV files - Beautiful Dark Mode

About

ML_Engineering

Features
Read full description

Become a machine learning engineer—starting exactly where you are. ML_Engineering is a complete interactive learning environment for iPhone, iPad, and Mac. Begin with basic arithmetic, examples, features, labels, and your first prediction baseline. Progress through Python, NumPy, pandas, statistics, feature engineering, classical machine learning, deep learning, computer vision, NLP, forecasting, recommendations, model serving, MLOps, monitoring, responsible ML, distributed training, LLM systems, and principal-level ML architecture. LEARN BY DOING • 40 structured courses from beginner to advanced • 400 substantive interactive lessons • 140 editable, syntax-highlighted code labs • 100 quizzes with validation and explanations • 80 architecture decisions based on production trade-offs • 80 guided concept exercises • Progressive hints that help without giving away the answer BUILD A SERIOUS ML PORTFOLIO Complete 40 practical projects: 12 Beginner, 14 Intermediate, and 14 Advanced. Build baselines, classifiers, forecasts, recommenders, vision and language models, feature stores, inference services, experiment systems, model registries, drift monitors, ML delivery pipelines, distributed training, LLM evaluation, governance controls, and a principal ML platform design. Every project includes an editable workspace, four milestones, checks, and outcomes you can explain in an interview. YOUR PRIVATE ML ENGINEERING TUTOR Ask from any lesson or project. Tutor Core can begin with basic arithmetic, define every new term, explain how models learn, diagnose code and architecture, and continue until the idea clicks. Offline Core is included and never sends questions anywhere. Compatible devices can add private Apple on-device generation. API, Ollama, and LM Studio connections are always optional. WATCH YOUR ML SYSTEM TAKE SHAPE Every completed lesson, course, and milestone advances a living ML-system construction scene—from problem framing and a baseline through features, training, serving, monitoring, and production guardrails. DESIGNED FOR SERIOUS PROGRESS Earn XP, build streaks, bookmark material, track role readiness, choose daily goals, switch between light and dark interfaces, and move naturally among iPhone, iPad, and Mac. FREEMIUM AND PRO Explore the first module of every course for free, keep your learning progress, and upgrade only when you are ready. ML_Engineering Pro unlocks the complete curriculum, every lab and portfolio project, and contextual Tutor access across iPhone, iPad, and Mac. Choose a monthly plan with a 14-day free introductory trial or an annual plan with a 7-day free introductory trial, when eligible. Prices are shown before purchase. Payment is charged to your Apple Account after confirmation. Subscriptions renew automatically unless cancelled at least 24 hours before the end of the current period. Restore purchases or manage your subscription directly from the app. Terms of Use: https://www.apple.com/legal/internet-services/itunes/dev/stdeula/ Privacy Policy: https://github.com/lukekevinmclaughlin-oss/ML_Engineering/blob/main/PRIVACY.md

Screenshots

Karnaugh & Boolean Minimizer4 screens
ML_Engineering4 screens

Verdict

The call

The clearest difference is price: ML_Engineering at Free against Karnaugh & Boolean Minimizer's $3.99. Karnaugh & Boolean Minimizer's advantage is in-app purchases (none vs 1) and chart position (#185 vs unranked). On update cadence, ads and device support there is nothing between them.

Scored on Price · Rating · Positive reviews · Number of ratings · Update frequency · Ads · In-app purchases · Monetization · Best chart rank · Devices · Requires iOS

CostPrice · In-app purchases · Ads · Monetization

ML_Engineering is free to download; Karnaugh & Boolean Minimizer costs $3.99 up front. ML_Engineering sells 1 in-app purchase, starting at $1.99 per month. Karnaugh & Boolean Minimizer asks for nothing beyond the download.

UpkeepUpdate frequency

Karnaugh & Boolean Minimizer ships an update monthly, ML_Engineering every 3 weeks. The most recent releases landed on October 11, 2026 and October 9, 2026 respectively.

Scorecard4 real differences · 7 level
Karnaugh & Boolean Minimizer versus ML_Engineering: the parameters behind the verdict, then further details
ParameterKarnaugh & Boolean MinimizerML_Engineering
Price$3.99Free — better
Rating4.2 (22 ratings) — better—
Positive reviews70.6% of reviews—
Number of ratings22 — better—
Update frequencyMonthlyEvery 3 weeks — better
AdsNoNo
In-app purchasesNo — betterYes
MonetizationPaid—
Best chart rank#185 — better—
DevicesiPhone, iPad, iPodiPhone, iPad, Mac
Requires iOS11.0 — better17.0
Further details — not scored
Size6 MB5 MB
Age rating4+4+
DeveloperKetan AppaLuke Mclaughlin

In-app purchases

None

Karnaugh & Boolean Minimizer

No in-app purchases

1 purchases

ML_Engineering

Subscriptions1
  • ML_Engineering Pro14 Days trial$1.991 Month

Questions

Is Karnaugh & Boolean Minimizer free?
Karnaugh & Boolean Minimizer costs $3.99, with no in-app purchases.
Is ML_Engineering free?
ML_Engineering is free to download, with in-app purchases available.
Do Karnaugh & Boolean Minimizer or ML_Engineering have ads?
Neither Karnaugh & Boolean Minimizer nor ML_Engineering shows ads.
Which is updated more often, Karnaugh & Boolean Minimizer or ML_Engineering?
Karnaugh & Boolean Minimizer ships an update monthly, and ML_Engineering every 3 weeks. Most recently, Karnaugh & Boolean Minimizer was updated on October 11, 2026 and ML_Engineering on October 9, 2026.

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