{"id":19120801,"url":"https://github.com/kongruksiamza/machinelearning","last_synced_at":"2025-04-06T17:12:58.871Z","repository":{"id":37714884,"uuid":"251460002","full_name":"kongruksiamza/MachineLearning","owner":"kongruksiamza","description":"โค้ดประกอบเนื้อหา Python Machine Learning เบื้องต้น 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id=\"badges\" align=\"center\"\u003e\n\n  [![Youtube KongRuksiam Tutorial](https://youtube-stats-card.vercel.app/api?channelid=UCB6eDEzpqpiaZnDMzoje57Q\u0026layout=extruded\u0026theme=neon)](https://www.youtube.com/@KongRuksiamTutorial)\n\n  \u003ca href=\"https://www.facebook.com/KongRuksiamTutorial\" target=\"_blank\"\u003e\n    \u003cimg src=\"https://img.shields.io/badge/Facebook-1877F2?style=for-the-badge\u0026logo=facebook\u0026logoColor=white\"/\u003e\n  \u003c/a\u003e\n    \u003ca href=\"https://www.udemy.com/user/kong-ruksiam/\" target=\"_blank\"\u003e\n    \u003cimg src=\"https://img.shields.io/badge/Udemy-A435F0?style=for-the-badge\u0026logo=Udemy\u0026logoColor=white\"/\u003e\n  \u003c/a\u003e\n    \u003ca href=\"https://www.youtube.com/@KongRuksiamOfficial/store\" target=\"_blank\"\u003e\n    \u003cimg src=\"https://img.shields.io/badge/Shopee-EE4D2D?style=for-the-badge\u0026logo=Shopee\u0026logoColor=white\"/\u003e\n  \u003c/a\u003e\n  \u003ca href=\"https://medium.com/@kongruksiam\" target=\"_blank\"\u003e\n    \u003cimg src=\"https://img.shields.io/badge/Medium-12100E?style=for-the-badge\u0026logo=medium\u0026logoColor=white\"/\u003e\n  \u003c/a\u003e\n  \u003ca href=\"https://codepen.io/kongruksiamstudio\" target=\"_blank\"\u003e\n    \u003cimg src=\"https://img.shields.io/badge/Codepen-000000?style=for-the-badge\u0026logo=codepen\u0026logoColor=white\"/\u003e\n  \u003c/a\u003e\n  \u003ca href=\"https://www.tiktok.com/@kongruksiamstudio\" target=\"_blank\"\u003e\n    \u003cimg src=\"https://img.shields.io/badge/TikTok-000000?style=for-the-badge\u0026logo=tiktok\u0026logoColor=white\"/\u003e\n  \u003c/a\u003e\n  \u003cbr\u003e\n  \u003ca href=\"https://github.com/kongruksiamza\"\u003e\n    \u003cimg src=\"https://komarev.com/ghpvc/?username=kongruksiamza\u0026style=flat-square\u0026color=blue\" alt=\"kongruksiamza\"/\u003e\n  \u003c/a\u003e\n\u003c/div\u003e\n\n--- \n\n## พื้นฐานที่ต้องเรียนมาก่อน\n- [Python เบื้องต้น](https://youtube.com/playlist?list=PLEE74DyIkwElyKXAKxmHETTtaq99btEPf\u0026si=PWovkpO9hBo5x2Go)\n- [Numpy](https://youtu.be/MDA8SbfdLKA?si=IQpuUv61pta7y1RL)\n- [จัดการข้อมูลด้วย Pandas](https://youtu.be/SPdwqEPZ_EE?si=F9x0vYZ1jjvuUBwn)\n- [สร้างกราฟด้วย Python \u0026 Matplotlib](https://youtu.be/MIaO3atFaGM?si=btbxFQJ8OwBpmpzB)\n\n## สารบัญเนื้อหา\n| ตอนที่ |                   ชื่อหัวข้อ                   |\n|:----:|:------------------------------------------:|\n|   1  | รู้จักกับ Machine Learning                     |\n|   2  | รู้จักกับชุดข้อมูล (Data Set)                     |\n|   3  | Iris Data Set                              |\n|   4  | MNIST Dataset                              |\n|   5  | แสดงภาพตัวเลขด้วย Pylab และ Matplotlib       |\n|   6  | แสดงภาพตัวเลข MNIST Dataset (ตัวเต็ม)         |\n|   7  | เขียนโปรแกรมแบ่งชุดข้อมูล                       |\n|   8  | ไลบราลี่ Seaborn                             |\n|   9  | รู้จัก Linear Regression                      |\n|  10  | การกระจายข้อมูล (Scatter)                    |\n|  11  | สร้างโมเดล Linear Regression                |\n|  12  | สร้างโมเดลทำนายอุณหภูมิ                        |\n|  13  | การวัดประสิทธิภาพโมเดล                        |\n|  14  | Binary Classifier                          |\n|  15  | Gradient Descent                           |\n|  16  | เขียนโปรแกรมแบ่งชุดข้อมูล MNIST                 |\n|  17  | จำแนกข้อมูลเป็น 2 กลุ่ม (Binary Classification) |\n|  18  | Stochastic Gradient Descent (SGD)          |\n|  19  | Cross Validation                           |\n|  20  | Confusion Matrix                           |\n|  21  | Precision Recall และ F1-Score              |\n|  22  | การคำนวณหาเพื่อนบ้านใกล้สุด (K-NN)              |\n|  23  | การสร้าง KNN Model                          |\n|  24  | ทำนายโรคเบาหวานด้วย KNN พร้อมค่า K ที่เหมาะสม   |\n|  25  | ทำนายโรคเบาหวานด้วย KNN และวัดประสิทธิภาพโมเดล |\n|  26  | ทฤษฎีการจัดหมวดหมู่ด้วย Naive Bayes             |\n|  27  | สร้างโมเดลด้วย Gaussian Naive Baye           |\n|  28  | ทำนายรายได้ประชากรด้วย GaussianNB            |\n|  29  | การวิเคราะห์องค์ประกอบหลัก (PCA)               |\n|  30  | การใช้ PCA ทำงานร่วมกับโมเดล                  |\n|  31  | MNIST Dataset ทำงานร่วมกับ  PCA              |\n|  32  | การจัดกลุ่มด้วย K-Means(K-Means Clustering)    |\n|  33  | การประยุกต์ใช้ K-Means(K-Means Clustering)    |\n|  34  | การจดจำใบหน้า (Face Recognition)            |\n|  35  | แสดงข้อมูลใบหน้า (LFW Databset)               |\n|  36  | สร้างโมเดลด้วย SVM (Support Vector Machine)  |\n|  37  | รู้จักกับ Neural Network                       |\n|  38  | สร้างโมเดลจดจำตัวอักษรด้วย MLP                 |\n\n## 🎓 คอร์สเรียนที่น่าสนใจ [![Udemy](https://img.shields.io/badge/Udemy-A435F0?logo=udemy\u0026logoColor=fff)](https://www.udemy.com/user/kong-ruksiam/)\n- [สร้างแอพพลิเคชั่นด้วยภาษา Python (Real-World Projects)](https://www.udemy.com/course/python-real-world-projects/?referralCode=4D6784B6C4CF2CBB1892)\n- [สร้าง GUI Application ด้วย Python](https://www.udemy.com/course/python-gui-projects/?referralCode=CFE6A91D21C759EF13E1)\n- [พัฒนาเว็บด้วย Django Framework 4.x](https://www.udemy.com/course/django-framework-real-world-projects/?referralCode=63ED08A516BE8C4A93F7)\n- [พัฒนาระบบร้านค้าออนไลน์ด้วย Django Framework 4.x](https://www.udemy.com/course/django-framework-e-commerce/?referralCode=AFDB5F462F46815300C1)\n- [พัฒนา REST API ด้วย Django REST Framework](https://www.udemy.com/course/rest-api-django-rest-framework/?referralCode=3E81004F9DAE23131BC4)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkongruksiamza%2Fmachinelearning","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkongruksiamza%2Fmachinelearning","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkongruksiamza%2Fmachinelearning/lists"}