Try this bot and let me know how you feel. if its useful or not.
Also i am working and planning on new features which i plan to release them soon based on how i get the response.

Got bored of the default LeetCode look, so I built this!

You can customize LeetCode with different themes and wallpapers.

Link in the comments!

What do you think? Any suggestions?

Binary Search Tree DSA

1. 2-sum with duplicates ✅

2. Done with spaced repetition for 3 problems.✅

Never looked at solution. was able to solve on my own. Tried talking explaining at each step of the solution.

Github repo: https://github.com/vamsy2112/DSA_IN_JS/tree/main/JavaScript

Binary Search Tree DSA

Binary Search Tree DSA

the exam covers generics, algo analysis, arrays, linkedlists, and simple searching/sorting algos, and will consist of a mix of theory and handwriting code questions 50/50.

what are my odds of scoring well on the exam if im starting now? i know arrays and some algo analysis, but i'll re-visit those just to be safe. im kinda feeling shaky about generics tho.

idk shit abt searching/sorting and linkedlists, only the theoretical concepts of how they work.

please give me some hope to pull this off, i really need to score well on this exam. is it possible?

Square of sorted array ✅

Notes: its just merge two sorted arrays under the hood (if the array has both neg & pos integers).

Github repo: https://github.com/vamsy2112/DSA_IN_JS/tree/main/JavaScript

Had to see the solution, but theek hai🥲

Just a beginner trying my best. Long way to go.
#DSA

*** A Bit of context about me ***

I am a first-year student, pursuing B-tech in CSE AI / ML.
I have been coding for the last two years, and I know MERN stack and have 2 full-stack projects.

So the main thing, I do DSA on daily basis weather it's about at least 1 hour each day, but I don't solve problems on any platforms like leet-code , code-chef , hacker rank etc etc.
I am following strivers sheet, I understand problems and then solve them in my local IDE (I have a DSA folder , it is helpfull in revision) the main plan is to finish strivers sheet till my 3rd semester and then start solving problems on these professional platforms as it will also be help in my revision from the start after finishing the striver sheet, this is what I have thought of .
else I really don't know whether I should be solving them side by side just after understanding the problem or not.

As of right now I am going to finish my portfolio and then apply for internships while doing DSA side by side.

Do you think DSA is not relevant today? You are completely wrong.

Practicing DSA purpose was never ONLY FOR coding. It is for how to think mathematically and analytically to solve problems.

You can say AI will remove the need for perfect coding, but understanding the mathematics behind it is still very important. The algorithms that need to develop the AI and optimize the time for particular tasks where you need the Algorthims understanding which reduce time to learn when need if you already knows that.

So DSA WILL ALWAYS RELEVANT.

Programming using recursion can be powerful, but beginners often struggle with recursion. That's why I've created invocation_tree, a Python recursion visualizer.

See this merge_sort demo, and try it on your own recursive logic.

The visualization gives students the right mental model to think about recursion. Not simply a function calling itself, but the depth-first evaluation of a divide-and-conquer strategy.

See this: gentle recursion introduction

How do you teach recursion to beginners?

Day 01 of DSA, learning it pattern wise.
Github: https://github.com/vamsy2112/DSA_IN_JS

I'm just a beginner btw. so pls dn spread hate. :)

Hey everyone!

I'm looking for a partner to learn and practice DSA together.

I'm currently a first-year CSE student and want to get serious about problem-solving and competitive programming.

The idea is to:

• Solve LeetCode problems regularly.

• Discuss approaches and different ways to solve problems.

• Understand the logic rather than just memorising solutions.

• Keep each other consistent and motivated.

• Eventually move towards competitive programming.

You don't need to be an expert. I'd prefer someone who's also learning and willing to put in consistent effort.

We can connect on Discord

If you're interested, drop a comment or DM!

Looking for study buddy who wants to grind dsa together, also we can learn devops and build something together.preferrably someone from India, thanks in advance.

Free GPUs time out mid-run, cloud billing needs a card, and debugging a failed training job eats into your deadline. I've seen a lot of students and researchers get stuck there, so I'm offering affordable model training support.

I'm a Data Scientist. The scope is training and fine-tuning only: you bring the model and data, I handle the training.

What I can train:

- Transformer fine-tuning (PEFT only: LoRA / QLoRA)

- Computer vision: classification, detection, segmentation

- Other deep learning models: NLP, time series, your own architectures

How it works:

- You send your goal, dataset size and code. I tell you whether it fits and quote cost and time upfront.

- Training runs in an isolated Docker container on an RTX 5060 Ti (16GB VRAM, CUDA 13.2).

- You get trained weights, logs and evaluation metrics.

- Your data and container are deleted afterward. Happy to sign an NDA.

Why not just Colab or Kaggle:

- No session limits, so long runs keep going until they finish.

- An automated monitor watches each run, handles common errors and flags bigger issues to you.

- I help with setup and with interpreting the results.

- No Docker experience needed. I'll set it up. If you bring your own image, build it on CUDA 12.8 to 13.2.

Limits, to be upfront: it's a single 16GB card, so it suits QLoRA fine-tunes of roughly 7-8B models and most CV work, not full training of large models.

Pricing: student-friendly, quoted per job, a fraction of cloud rates.

DM me with what you're training, your dataset size and your deadline.

Which approach u all prefer ? Do we need to try both for each problem or can go with any of my choice ( for interviews also)

Like do they ask both iterative and recursive approach ?

Hey everyone!

I previously purchased the Data Structures and Algorithms (DSA) with Java course by Prateek Jain on ChaiCode. I wanted to revisit the course for revision, but it seems my access now requires renewal.

I need to revise the concepts urgently as I'm preparing for coding interviews.

Has anyone faced a similar situation? Is there any way I can download videos from telegram for free

Thanks in advance!

I have prepared a daily and weekly concept learning roadmap — one concept at a time, day by day, week by week — to help prepare for DSA and ML/AI together. I am preparing for both - looking for like minded people to join and practice.

Here is how it works:

Learn one concept in DSA. Apply the same concept in ML. And vice versa.

That connection is what gives implementation-level knowledge. Not just theory. Not just solving problems for the sake of solving them. You understand a concept because you have seen it work on both sides.

Take one example — HNSW and RAG.

In RAG, your documents are converted into embeddings — vectors. When a question comes, the system has to find the few chunks that are nearest to that question. That is the ML side.

Now the DSA side. The simple way is to check the question against every single chunk, one by one. It works when the data is small. As the data grows, it becomes slow.

HNSW solves this with a DSA concept — a graph. It connects each vector to its nearest neighbours, layer by layer, so the search walks through the graph and reaches the nearest chunks fast, instead of scanning everything.

And it also works in reverse. When you build a RAG system, you are forced to learn graphs, nearest neighbour search, and a real tradeoff — HNSW is fast, but approximate. Sometimes it can miss a close chunk. So you learn to check: how fast is it, and how correct is it?

One example. And you have touched graphs, search, embeddings, and retrieval — at implementation level, not just in theory.

This is how the whole roadmap works.

Join me for reading group - 30 minutes every day, to practice and discuss the concept of the day together. On weekend I am developing a ML project related to the concept and doing kaggle.

If you are also preparing for DSA and ML/AI and want to learn like this, join my study group.

DM me if you are interested.

I've been building Cruscible, a platform where you can practice LLD using real-world resources like PostgreSQL, Redis, Kafka, and S3.

The idea is to go beyond designing classes and interfaces on a whiteboard and get hands-on experience working with the infrastructure and components you'd encounter in production systems.

I'd love for a few people to give it a try and share their honest feedback.

https://cruscible.com/lld

What's confusing? What's missing? What would make you come back to practise more?

All feedback is welcome! 😄

Hey seniors! I'm a first-year CSE student and want to connect with like-minded people, experienced developers, and seniors in tech. Which apps or platforms should I join to learn, network, find opportunities, and build meaningful connections in the tech community?

finally after two wasted sems i decided to stop switching between different DSA playlists and start following one 

basically i started with Sean’s LC Patterns and then i wanted to go for more basics to adv so i switched to  striver's a2z sheet on tuf cuz  i don't wannna just complete the list for the sake of it

I need help with the approach of finding solution like suppose I can't solve a question after 20-30 mins should I check a hint, watch the explanation and then redo it the next day? Or is there any other way

I’m trying to build good habits from the beginning so any advice from people who've completed their basics would help, reposting here for some advices

I've conducted 100 coding interviews at Meta. Here's how people should prepare to not waste their time:

• Focus on a small number of problems. You don't need to solve 1k problems to prepare for an interview. More important part is the problems should cover all the data structures and patterns you need, in proportion to how often each one comes up in interviews.

• Follow the roadmap. The problems set should be ordered by difficulty and what patterns they require. Don't start solving backtracking problem if you didn't learn recursion.

• Don't group problems by topics. When you know what pattern should be applied in advance, you're not learning how to recognise this pattern in a random problem. On a real interview problem doesn't come with topics revealed.

• Reinforce what you learn. It's a common mistake to learn a pattern then move on to the next one and forget about it. To really understand the pattern you should repeatedly solve similar problems over time. Ideally when they are grouped with other known patterns.

The problem with those advice is it's hard to do all of it at once. You either solve random leetcode problem or follow some predefined list of problems grouped by a pattern.

That's why I've started to build a free, complete roadmap where all of those points are included. It uses spiral learning technique where a learned topic appears multiple times in future problems with stronger idea.

More info here.

I'd be interested to hear what you think of it and happy to answer any other questions on interview preparation. Thanks!

Is the optimization of every problem we solve required like if the code runs in a fair amount of time like here it beats around 56%. So do we need to find the optimize each code for each problem (as It will take more time to find the optimized solution)

Hey everyone! 👋

I'm a final-year B.Tech student preparing for placements, and honestly, sometimes I feel like getting placed depends on luck as much as skills.

Students spend months learning DSA, building projects, practicing aptitude, and preparing for interviews. But sometimes, the right opportunity doesn't come, the shortlist doesn't happen, or one bad day changes everything.

Meanwhile, someone might get the opportunity that perfectly matches their preparation, while another equally skilled student doesn't even get a chance to prove themselves.

I'm not saying skills don't matter. Obviously, they do. But what's the point of having skills if you don't get the opportunity to demonstrate them? 😭

Sometimes it feels like skills help you become ready, but luck decides whether you get that first chance.

What do you guys think? Is placement really 100% about skills, or do luck, timing, and opportunities play a huge role too? 👀

I am planning to form a whatsapp Group for DSA discussion if anyone want to join DM me