Learn how to build a CRM (Customer Relationship Management) App with Django, Python, and MySQL.

The app will use MySQL for the database. We'll be able to Register, Log In, Log Out, Add Records, View Records, Update Records, and Delete Records.

✏️ Course created by John Elder. Check out his channel: https://www.youtube.com/@Codemycom

💻 Github Code: https://github.com/flatplanet/Django-CRM

🔗 MySQL Download: https://dev.mysql.com/downloads/installer/

⭐️ Contents ⭐️
0:00:00 Introduction
0:01:50 Installation and App Setup
0:06:45 MYSQL Configuration
0:13:18 Version Control Git and Github.com
0:18:14 Build Out The Basic App
0:28:46 Login Users
0:47:32 Logout Users
0:51:45 Register Users
1:15:00 Database Model
1:25:48 View Records On Website
1:31:01 Bootstrap Table
1:38:23 Individual Records
1:48:41 Bootstrap Card
1:56:51 Delete Record
2:01:05 Add New Records
2:12:10 Update Records
2:20:06 Push Code To Github
2:20:54 Conclusion

🎉 Thanks to our Champion and Sponsor supporters:
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Перевод: Алексей Лоскутов
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У відео йдеться про історію винайдення комплексних чисел, які стали вирішенням проблеми від'ємної площі в геометрії і зумовили відмову від геометрії як основи алгебри. Зрештою комплексні числа стали незамінними у фундаментальній фізиці - у рівнянні Шрьодінґера, яке описує хвильову функцію.

✅Текст читав: Андрій Горбунов (канал “Лакуна”)
✅Переклад: Марія Луценко, Марія Ковальчук, Артем Панченко, Катерина Рибачок, Анастасія Євгенова, Анастасія Цьосенко.
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This is the 1st video in a series on using large language models (LLMs) in practice. I introduce LLMs and three levels of working with them.

▶️ Series Playlist: https://www.youtube.com/playli....st?list=PLz-ep5RbHos
📰 Read more: https://towardsdatascience.com..../a-practical-introdu

Music by Me
https://soundcloud.com/shawhin....-talebi/letsalljustt
https://www.youtube.com/@shawhin-music

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Homepage: https://shawhintalebi.com/

Intro - 0:00
What is an LLM? - 1:13
Zero-shot Learning - 3:36
How do LLMs work? - 5:44
3 Levels of Using LLMs - 7:52
Level 1: Prompt Engineering - 8:22
Level 2: Model Fine-tuning - 11:00
Level 3: Build your own - 13:13

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This chatgpt for digital marketing course will guide you will essential techniques for seo and content creation for your digital marketing needs.
ChatGPT revolutionizes digital marketing by streamlining content creation across platforms through its engaging blogs, social media posts, and persuasive copywriting, while also fostering customer engagement via instant responses on social media, personalized user experiences, and efficient automated customer support; it further aids in SEO efforts by suggesting relevant keywords, enables trend analysis for strategic insights, assists in content localization for global reach, facilitates the creation of interactive content like quizzes and polls, and even contributes to A/B testing variations, all of which collectively empower marketers to enhance efficiency, engagement, and overall campaign success.

00:00 ChatGPT For Digital Marketing
04:03 ChatGPT for marketing
14:22 How to use chatgpt for SEO
01:06:00 ChatGPT for content creation
01:10:20 Master SEO Content with ChatGPT
01:20:00 ChatGPT use cases
01:47:40 ChatGPT for Business
01:51:50 How to make money using chatgpt

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Correction (10:26). The probabilities are wrong. The correct ones are here:
For Die 1: 0.4^4 * 0.2^2 * 0.1^1 * 0.1^1 * 0.2^2
For Die 2: 0.4^4 * 0.1^2 * 0.2^1 * 0.2^1 * 0.1^2
For Die 3: 0.1^4 * 0.2^2 * 0.4^1 * 0.2^1 * 0.1^2

Kullback Leibler (KL) divergence is a way to measure how far apart two distributions are.
In this video, we learn KL-divergence in a simple way, using a probability game with dice.

Shannon entropy and information gain: https://www.youtube.com/watch?v=9r7FIXEAGvs&t=1066s&pp=ygUic2hhbm5vbiBlbnRyb3B5IGluZm9ybWF0aW9uIHRoZW9yeQ%3D%3D

Grokking Machine Learning book: www.manning.com/books/grokking-machine-learning
40% discount code: serranoyt

For more information about Stanford’s graduate programs, visit: https://online.stanford.edu/graduate-education

November 21, 2025
This lecture covers:
• LLM-as-a-judge overview
• Best practices and benefits
• Biases and pitfalls

To follow along with the course schedule and syllabus, visit: https://cme295.stanford.edu/syllabus/

Chapters:
00:00:00 Introduction
00:07:08 Inter-rater agreement metrics
00:18:24 Rule-based metrics
00:21:00 METEOR, BLEU ROUGE
00:28:00 LLM-as-a-judge
00:33:44 Structured outputs
00:36:48 Variants
00:38:47 Position, verbosity, self-enhancement bias
00:47:22 Best practices
00:54:06 Factuality
01:00:15 Agent evaluation
01:23:50 Benchmarks
01:25:12 Knowledge with MMLU
01:29:34 Reasoning AIME, PIQA
01:33:57 Coding with SWE-bench
01:36:15 Safety with HarmBench
01:40:51 Agents with Tau-Bench

Afshine Amidi is an Adjunct Lecturer at Stanford University.

Shervine Amidi is an Adjunct Lecturer at Stanford University.

View the course playlist: https://www.youtube.com/playli....st?list=PLoROMvodv4r