Large Language Models are powerful but they can also be unpredictable and give responses in all sorts of formats.
But the Pydantic Python library lets you define the shape and form of both inputs and outputs.
In this guide, @manishmshiva teaches you how to keep your LLM outputs predictable using Pydantic validation.
https://t.co/LrOE1C93cm
Learn how to analyze multimodal data with LLMs and Python. This tutorial covers:
- Classifying text with LLMs
- Answering questions about images
- Transcribing audio data (speech) to text
- Building a natural language query interface over an SQL database
https://t.co/mHuaDkXSrL
A famous formula for π:
π/4 = 1 − 1/3 + 1/5 − 1/7 + …
This comes from a trigonometry formula:
arctan(x) = x − x³/3 + x⁵/5 − x⁷/7 + …
Putting x = 1 gives the series for π/4.
This result was discovered independently by: Gottfried Wilhelm Leibniz (1673), James Gregory (1671), Nilakantha Somayaji (around 1500, in Tantrasangraha).
When you're working with AI tools, you typically have to send your files to third-party servers.
But this may not work for you if you're dealing with sensitive information.
In this guide, @techno0ptimist teaches you how to run an LLM locally to interact with your documents.
https://t.co/E2zj49sSGn
If you’re hardcoding AI prompts in your mobile or web apps, you might be at risk for prompt theft and injection attacks 😓⚠
Learn how to move your gen AI prompts and configurations from the client-side and onto Firebase servers to help improve security and iterate faster using Firebase AI Logic.
Chapters:
0:24 - Firebase AI Logic
0:51 - Server Prompt Templates
2:07 - Creating templates
4:51 - Using templates in your app
5:45 - Creating new template versions
Introducing Operation Matrix
Because Matrix operations generally break kids’ brains on whiteboards… Matrices aren't just numbers- they are transformations in space
Now can actually SEE the geometry: every addition, multiplication, inverse, eigenvalue, and eigenvector becomes a transformation in real-time space.
What it visualizes:
• Basic ops (add/subtract/multiply)
• Transpose, Invert, Adjugated
• Cross products + Determinant
• Matrix powers + Eigenvalues/Eigenvectors
#LinearAlgebra #CreativeCoding #ThreeJS #ReactThreeFiber #MathVisualization #EdTech #WebGL #STEM @reactthreefiber@threejs
Valuation of firm depends on stage in its life cycle and the purpose of valuation.
I tell my clients: tell the reason you need valuation I’ll give you approach.
Look at full perspective:
There are 6 stages:
1. Starup
2. Young growth
3. High growth
4. Mature growth
5. Mature stabile
6. Decline
Before valuation it is useful to determine which stage company belongs in.
For example, if the company is in mature growth stage then:
• Source of Value is stabile earning potential
• DCF is applicable
• Relative valuation is applicable too
• Pricing measure are : Revenues, Earnings, Growth rate, FCF
• Valuation ratios could be : PE to Growth rate, P/E, EV/FCF
• Preferable method:
👉 DCF
👉 𝘈𝘭𝘵𝘦𝘳𝘯𝘢𝘵𝘪𝘷𝘦 𝘰𝘳 𝘥𝘰𝘶𝘣𝘭𝘦 𝘤𝘩𝘦𝘤𝘬:
• Comparable companies (P/E)
• Comparable transactions – EBITDA multiple
The success of valuation lays in how well you create a projection of each important financial categories
Look the other stages a well.
~~~~~~~~~~~
Want to master valuation through powerful financial models?
Check my courses:
👉 https://t.co/QjYpmVagXE
See you there!
The Normal Distribution (also called the Gaussian distribution) is a fundamental concept in Statistics and probability. It describes how many real-world measurements naturally spread around an average value.
The Normal Distribution (also called the Gaussian distribution) is a fundamental concept in Statistics and probability. It describes how many real-world measurements naturally spread around an average value...