Learn Machine Learning & AI vs PC 110

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.

PC110 Atlas is an interactive museum, hardware explorer, and emulator host dedicated to the palm-size PC that arrived in 1995. RUN YOUR OWN MACHINE Bring firmware and system media that you lawfully obtained from your own hardware. Package Import verifies a single ZIP and installs all recognized files together. Advanced Import lets experienced users manage each file individually. No firmware, operating system, or PersonaWare image is included. RUN IT ON MAC Use the complete emulator and research library on macOS 14 or later. Select BIOS, hard-disk, floppy, and CD images with the standard Mac file picker. Imported media remains inside the app sandbox unless you choose another file. USE THE WHOLE KEYBOARD The full PC110 console becomes a touch surface. Every visible key and colored control maps to the emulated machine, including the distinctive Japanese key layout and two-part Enter key. CONTROL IT FROM APPLE WATCH The included Apple Watch companion mirrors the live PC110 display and guest audio from the paired iPhone, provides pointer and keyboard controls, and offers shortcuts for all sixteen original PersonaWare launcher applications. Fit shows the complete display, while zoom and pan make small guest controls easier to read. QEMU and imported media remain on the iPhone. EXPLORE THE HARDWARE Orbit a detailed 3D reconstruction of the mainboard, pinch to zoom, separate the stack, fade individual copper layers, and reveal the component overlays on both sides. Switch to annotated board views to learn how the 486SX, SCAMP IV, Bowman, Pluto, VGA, audio, storage, and PC Card subsystems work together. FOLLOW THE SCHEMATIC Navigate the reconstructed schematic by functional sheet, then zoom and pan through the original vector evidence without relying on optical captures. ENTER THE ARCHIVE Discover the machine through a factual timeline, original design notes, an illustrated PersonaWare history, and direct links to the open hardware project. PC110 Atlas is an independent historical and preservation project. IBM and the IBM logo are trademarks of International Business Machines Corporation. PersonaWare and other product names belong to their respective owners. The app is not affiliated with or endorsed by IBM.