Machine Learning

LiveSoftecks257 apps · 6.5M installsEducationFree · contains adsin.softecks.machinelearning

Learn machine learning, AI, models & ML tools offline.

Alert me★ WatchOpen in Play ↗
Total installs
2,571
exact · Play shows 1,000+
Installs / day
0
7-day avg · last day 0
Rating
—★
— ratings · — reviews
Released
9 Mar 2021
5.6y ago
Last update
17 Sept 2026
v2.1 · 27d ago
Countries
—
not checked yet

Installs per day

gain of the exact counter

No change in the counterOur first day-to-day reading of the counter. The line starts with the next one.

Daily tracking since 11 Oct 2026 · history grows every day

Install history

exact counter from Google Play
2,5702,5712,57211 Oct12 Oct
05001,0001,5002,0002,5003,0009 Mar 202111 Oct 202612 Oct 2026

Dashed: estimate from the release date (no daily data before 11 Oct 2026) · time axis compressed before that day

Daily tracking since 11 Oct 2026 · history grows every day

Change timeline

Full history

No changes recorded yet. We compare every crawl with the previous one and list title, icon, screenshots, description, version, price and availability changes here.

Country availability

Availability has not been checked for this app yet. “Check all countries” looks the app up in about 140 Google Play storefronts and shows where it is live, listed but not installable, or missing — plus any country-specific (custom) store listings.

Top countries

Country data will be available soon.

We estimate where downloads come from using the app’s position in Google Play’s top charts in about 140 countries. This app is not in any chart we have collected yet; the estimate appears as soon as it is.

Top chart positions

Not in any tracked top chart.

App manifest

Read this app's manifest from Google Play: permissions, declared SDKs, components and AdMob app ID. Saved analysis appears here automatically.

Manifest analysis reads only the required APK ranges. Base APK downloads may need separate device splits to install.

Data safety

declared by the developer on Google Play
  • Shares data with third parties Device or other IDs
  • No data collected
  • Data is encrypted in transit
  • No way to ask for data deletion

This is the developer's own declaration, summarised from the Play listing. The permissions below show what the app is technically able to access.

Permissions

5 in 1 group
0 Sensitive1 Notable4 Routine
OtherNotable5

Access to miscellaneous device features that don't fit other categories

  • Keep your phone's processor or screen from going to sleep, which can use more batteryprevent device from sleeping · WAKE_LOCK
  • Check whether you are online and whether you use Wi-Fi or mobile dataview network connections · ACCESS_NETWORK_STATE
  • Connect to the internet to load content and send datafull network access · INTERNET
  • Make your phone vibratecontrol vibration · VIBRATE
  • Receive push messages sent from the app's servers over the internetreceive data from Internet · com.google.android.c2dm.permission.RECEIVE

Sensitive = can reach personal data, location, camera/mic or act on your behalf. Notable = changes how your device behaves. Routine = normal for almost every app. Source: Google Play's permission list for all versions of this app.

Store listing

Full description
Machine Learning is an AI and ML learning app for students, developers, data science beginners and interview learners who want clear machine learning lessons with practical model tools. Confused by datasets, train-test split, feature scaling, regression, classification, metrics or gradient descent? This app turns machine learning into a structured study path so you can understand core ideas, revise offline, and use calculators for exams, projects, labs and interviews. ⚙️ Core Features Deep Dive ✅ 5 focused ML subjects Study Foundations & Learning Paradigms, Concept Learning & Version Spaces, Linear Models & Discriminants, Neural & Kernel Methods, Dimensionality, and Trees, Feature Selection, Lifecycle & Practice. The lessons help you move from “what is ML?” to how models learn, generalize and make predictions. ✅ Clear concept explanations Learn supervised, unsupervised and practical learning ideas through simple reading sections. Topics include hypothesis spaces, version spaces, regression, classification, decision functions, MLPs, RBF networks, SVMs, feature selection, decision trees, lifecycle steps, applications and common pitfalls. ✅ 21 included ML tools Practice with calculators for train-test split, dataset size, feature scaling, min-max normalization, z-score standardization, MSE, RMSE, MAE, R-squared, accuracy, precision, recall, F1 score, confusion matrix, Euclidean distance, Manhattan distance, cosine similarity, KNN distance, linear regression, logistic sigmoid and gradient descent. ✅ 30 How-To lessons Use practical How-To content to understand model preparation, dataset handling, metric interpretation, feature scaling, regression basics, classification checks and the steps learners often need before building real ML projects. ✅ Offline, bookmark and search Read lessons without internet, bookmark difficult topics, and search machine learning, AI, regression, classification, SVM, decision tree, feature scaling, accuracy, precision, recall and model evaluation quickly. 👥 Who Is This For? • Students can revise machine learning fundamentals before exams, viva sessions, lab records and classroom discussions without opening multiple websites. • Developers can understand ML workflow terms before using Python libraries, notebooks or AI frameworks in real projects. • Data science beginners can build confidence in metrics, dataset preparation, normalization, regression, classification and model performance evaluation. • Interview learners can quickly review accuracy, precision, recall, F1 score, confusion matrix, SVM, decision trees and gradient descent from one offline reference. 💡 Why Choose Machine Learning? Many learning resources are too scattered, too mathematical or too code-heavy for beginners. Machine Learning combines lessons, How-To topics, bookmarks, fast search and practical calculators in a clean mobile format. It helps learners connect theory with model evaluation and makes revision faster during study sessions. ❓ Frequently Asked Questions Q: Can I learn machine learning offline? A: Yes. Lessons can be accessed offline, making the app useful for travel, classrooms, low-connectivity areas and revision. Q: Does this app include ML calculators? A: Yes. It includes 21 tools for dataset splitting, scaling, regression error, classification metrics, distance measures, KNN, sigmoid and gradient descent. Q: Is this useful for AI and data science beginners? A: Yes. It explains machine learning foundations, linear models, neural methods, SVMs, decision trees, feature selection and lifecycle practice. Q: Is this a live coding IDE or model trainer? A: No. It is an educational learning and reference app with study tools. It does not train real models, run notebooks, provide datasets, or replace production ML libraries. 🚀 Download Machine Learning today and start learning machine learning, AI, datasets, regression, classification, SVM, decision trees, model metrics, gradient descent and ML tools offline.

What's new

✅ Enjoy 21 newly added tools along with overall performance improvements, completely for free.

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