https://preview.redd.it/vmad1cko27bh1.png?width=1920&format=png&auto=webp&s=0dbde08f6f1e80b56436e7dbeb637cf45f3681c2

i opened my molab marimo notebook today but its shwoing this error , does molab servers are down or i am only the one facing issues?

I am new to this community and I have seen most of the player shouting the name dojo players. What does that means ?

Hello, bhai log, feeling very depressed and sad , my preperation did not went well for this year so many distractions , and my lazy bad habit leads me to the failure of not qualifying for JEE advanced and and did cleared WBJEE as well .

​

I got 59k rank in WBJee which is very low, I don't know I can get a good college for cse in Ai and Ml .

My jee score was below 60 percentile and yeah , I lost all my hope .

Samjh nhi aa rah ab kya karu , saamne sab kuch blank sa lag raha hai.

Hi everyone,

I'm a student with no dedicated GPU or powerful PC right now (just basic integrated graphics). I want to learn and practice:

\- Video editing (Premiere Pro / DaVinci Resolve)

\- AI image generation (Stable Diffusion, ComfyUI, Flux z image, and qwen image and upcoming new models, etc.)

\- Running local LLMs (Ollama, LM Studio — starting with 7B-13B models, maybe up to 30B quantized later)

\- 3D animation (Blender modeling, rigging, rendering with Eevee/Cycles)

I know these tasks benefit a lot from a good NVIDIA GPU (for CUDA support in AI and video/3D tools), decent VRAM (at least 12GB+ recommended for comfortable AI work), plenty of system RAM (32GB minimum, 64GB ideal), a modern multi-core CPU, fast NVMe SSD, and good cooling.

\*\*My situation:\*\*

\- Budget: I'm a student, so I'm hoping for something reasonable — ideally under $1000–1500 USD if possible (or equivalent in my local currency). I'm open to used/refurbished parts (especially GPU like RTX 4060 Ti 16GB, 3080/3090, or newer budget options) to stretch the budget. Willing to go a bit higher if it's a solid long-term build with upgrade path.

* \- Location: india/kolktata — suggestions with local availability (Amazon, local shops, etc.) would be awesome.

\- Priorities: Good performance for learning without extreme overkill. Future-proofing where possible (AM5 platform or similar for upgrades). Low noise if possible since I'll be studying/editing in a small space.

I'm completely new to building PCs, so any help with a full parts list (CPU, Motherboard, RAM, GPU, Storage, PSU, Case, Cooler) via PCPartPicker or similar would be amazing. Also happy with pre-built suggestions or mini-PC options if they can handle the workload reasonably.

Any advice on balancing the build for these creative/AI workloads would be super helpful — for example, how much VRAM I realistically need to start generating images and running local models without frustration.

Thanks in advance for any suggestions or builds you can share! Really appreciate the community's help. 🙏

Hey everyone,

Nice to see you again I am Utkarsh.

I wanted a clean, high-density, completely responsive way to study and review core probability concepts (spanning from basic sets up to Bayes' Theorem and Binomial Distributions).

Disclaimer not for Mobile user till now, I will update very soon for mobile optimization it's currently suitable for laptops and desktops.

📚 The Class 12 Educational Content Outline

The deck systematically covers the entire core advanced probability curriculum, structured to build intuitive understanding alongside rigorous mathematical proofs:

• Foundations & Counting Principles: Baseline sample spaces, events, and a deep-dive into Permutations & Combinations ($^nP_r$ and $^nC_r$) to solve complex arrangement problems.
• Set Theory Integration: Visualizing and calculating intersections, unions, and complements using Venn Diagrams, leading into De Morgan's Laws for event boundaries.
• Conditional Probability Architecture: Transitioning from unconditional spaces to constrained ones ($P(A|B)$), mapping structural changes in the sample space.
• The Multiplication Theorem & Independence: Differentiating between dependent structures and independent systems ($P(A \cap B) = P(A) \cdot P(B)$).
• Total Probability & Bayes' Theorem: Teaching students how to map inverse conditional paths—calculating posterior probabilities from prior data partitions.
• Random Variables & Distribution Parameters: Setting up probability mass functions (PMF) to evaluate the Center of Mass (Mean / Expected Value $\mu$) and the Dispersion Target (Variance $\sigma^2$ & Standard Deviation $\sigma$).
• Binomial Pipeline: Breaking down Bernoulli trials and modeling binary outcome pipelines over $n$ independent sequences.
• Alternative Likelihood Ratios: A clean breakdown of Odds in Favor vs. Odds Against, showing real-world translations from betting structures to medical risk tracking.

Standard presentation software kept messing up my LaTeX formatting or forcing awkward scrolling across deep layout configurations, so I custom-coded a 17-slide web deck using vanilla web tools.

Features:

• Frame-Locked Grid Layouts: Every complex mathematical calculation and proof matrix is systematically compressed to fit cleanly inside the viewport frame without vertical scrolling.
• Stochastic Theme Shifting: Every single page turn randomly selects and injects a unified neon custom-property color profile across the document root.
• Synchronized Progress Engine: The timeline bar dynamically tracks the progress state while adapting to the current page's active neon accent color.
• Pure MathJax Vector Integration: Crisp formula rendering across all structural math expressions.

Live Project Link: https://probability-notes.vercel.app

Would love to hear your feedback on the layout density, readability across different screens, or the overall theme transitions!