This skill encodes Emil Kowalski's philosophy on UI polish, component design, animation decisions, and the invisible details that make software feel great.

Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.

这是我自己做的一个类似滴滴打车的Android出行项目，主要针对滴滴等出行平台一直饱受质疑的“人车不符”问题，以及当前越发火热的或计划和出海战略，给出行项目增加了下面几个功能： 1. RFID识别验证功能：在司机证件或者车内识别硬件嵌入RFID识别芯片，乘客使用手机读取到芯片信息，并且通过网络发送到出行平台数据库进行验证（我用JNI加了一个C语言的MD5加密算法对识别到的信息进行了加密）。如果不是合规的“人”或“车”，则不能完成订单并向平台或监管单位汇报当前位置。（为了方便读者测试，可以使用手机读取任何一个加密或非加密RFID芯片，比如银行卡、公交卡等，我在代码中的验证前阶段把芯片信息都换成我自己的司机信息，确保读者测试时可以收到服务器的回复） 2. 海外版功能：点击切换当前语言。 3. 司机证件号码识别功能：读取司机证件上的证件号码，也可以用来与出行平台数据库的接单司机信息进行。I complete this whole project on my own . Including Android application programming，web server ( Apache + PHP + MySQL), and UI. 1．Map route planing。You can use mobile phone choose pick up & destination address，application provide address name hint and draw optimized route for user , then call car for you. 2．RFID authentication function：User can use application to scan driver license or other RFID hardware, then use NDK MD5 algorithm encrypt RFID number, and send it to Web Server Database, check with driver information and authenticate ID number , if ID number coherent with driver info , send back driver information to User and continue call car order . record user location and alert if ID not coherent. 3．Driver License Number Recognition : Application can recognize driver license digit number ,and also can send to web server for authentication & feed back result to user.

A program to recognize text on the screen

A very simple CNN project to recognize gestures made in American Sign Language

The project developed using TensorFlow to recognize the License Plate from a car and to detect the charcters from it.

Recognize tables and text from scanned images that contain tables. 从包含表格的扫描图片中识别表格和文字

Find and prioritize ethical backlink and digital-PR opportunities using SandBase DataForSEO backlink data. Use when asked to analyze backlink profiles, find referring-domain gaps, compare link competitors, or prepare a link-outreach target list.

Create a new SigNoz dashboard from a natural-language intent — import a curated template (PostgreSQL, Redis, JVM, k8s, hostmetrics, APM, LLM, etc.) when one fits, or build a custom dashboard from scratch with metric / trace / log panels. Make sure to use this skill whenever the user says "create a dashboard for…", "set up monitoring for…", "build me a dashboard…", "I need observability for…", "import a dashboard template", or asks to track / visualize a service, database, cluster, or AI/LLM platform — even if they don't explicitly say "dashboard". Also use it when someone wants to "monitor", "watch", or "see metrics for" a technology and the natural answer is a dashboard.

Generate North American road-trip itineraries as a map-first, offline-friendly single-file HTML page. Plans around daily driving segments, overnight stops, fuel/EV-charging, national-park reservations (Recreation.gov / NPS), seasonal road closures, and timezone/border crossings — for executable, decision-ready trips. Two entry modes: give a start + region/destination + days and it plans the whole route, or hand it an existing route and it verifies, fills gaps, and produces the page.