NumTest vs Learn Machine Learning & AI

The primary objective of this application is to provide researchers with a mechanism for testing and comparing the performance of their numerical solvers. This application includes algorithms capable of benchmarking values on a diverse range of scientific numerical problems. It is important to note that the results presented are for comparison purposes only and are not guaranteed to be correct. We will be adding more topics in the future. Please encourage us by sharing this app with your friends and colleagues. Your support is greatly appreciated! If you have any questions or feedback, please contact us at daniel.hadush@gmail.com. Thank you for your interest!

Learn Machine Learning & AI takes you from "what is machine learning" to understanding the algorithms behind modern artificial intelligence — 105 subjects and 2,650 lessons, in pieces short enough to read on a phone. No prior AI experience required. If you can follow basic algebra and a little Python, you can follow this course. WHAT YOU WILL LEARN Machine Learning Foundations — how machine learning differs from traditional programming, the training workflow, test data, overfitting, underfitting, bias and variance, and how models are evaluated. Supervised Learning — linear and logistic regression, decision trees, random forests, support vector machines, k nearest neighbours and naive Bayes, each with the intuition behind it. Unsupervised Learning — k means and hierarchical clustering, dimensionality reduction, principal component analysis and anomaly detection. Deep Learning and Neural Networks — perceptrons, activation functions, backpropagation, convolutional networks for images, recurrent networks and LSTMs for sequences, and an introduction to transformers. Reinforcement Learning — agents, environments, rewards, Q learning and policy based methods, without heavy mathematics. Natural Language Processing — tokenization, embeddings, sentiment analysis, and how large language models are built on these ideas. Tools and Libraries — where Python, TensorFlow, Keras, scikit learn, NumPy, Pandas, H2O, OpenCV and Spark MLlib fit into a real workflow. Applied Machine Learning — healthcare, finance, recommendation systems, fraud detection, computer vision and forecasting. TEST WHAT YOU HAVE LEARNED Over 8,000 quiz questions across all 105 subjects. Ten questions per session, four options each, tied to the chapter you have been reading. Three timed difficulty levels: beginner 30 seconds per question, intermediate 20, expert 10. A session runs 5:00, 3:20 or 1:40. Pass at 70%. Filter by level, by attempted or untried, and by best score, so practice targets the algorithms you have not yet understood. Every attempt is stored. ML INTERVIEW PREPARATION 25 machine learning roles with 100 questions each — 2,500 in total — from junior ML engineer through senior, staff and principal, plus data scientist, applied scientist, MLOps, NLP and computer vision. Timed like a real screening round, scored, and saved so you can retake and compare. STUDY OFFLINE Download any subject for offline reading. Lesson text is stored on the device and stays available with no connection; images still need network. Anything you open is cached automatically. The Downloads screen shows what is saved and lets you cancel, resume or remove a subject. PROGRESS, STREAKS AND CERTIFICATES Mark lessons complete, watch the progress ring fill on every subject, and use the Continue card to return to exactly where you stopped. A daily streak counts every day you study, with an optional reminder that is off by default. Complete a subject and pass its quiz at 70% or above to unlock a certificate you can save and share. BUILT FOR LEARNING ON A PHONE Plain language first, mathematics second — every algorithm is explained in words before any notation appears. Short sections you can finish in a few minutes. Syntax highlighted code with one tap copy. Search across the whole course. Bookmarks and history, light, dark and system themes, adjustable font size, and tablet layouts. WHO IT IS FOR Students who want a second explanation when the lecture did not land. Developers moving into machine learning engineering or data science. Candidates preparing for ML and data science interviews, where the questions are still mostly about fundamentals. Professionals who need to understand what an AI system in their industry is actually doing. No video to buffer. No account required. Open your first lesson today. Questions, corrections or a topic request? Email mail@ehsanur.com — we update the app based on what learners ask for.