Gaurav More
@gauravmoretech
Software Engineer. AI/ML/Data Science. Tech is Oil #techtwitter
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What fascinating about programming is that you are going to develop software out of thin air and it will be used in future by people around the world...!!!
a video so goated that it helped me overcome my fear of mathematics
Basic roadmap to become a Quant: Linear Algebra ↓ Numerical Methods ↓ Probability and Statistics ↓ Multivariate Analysis ↓ Mathemarical Modeling ↓ Optimization ↓ Scripting Programming ↓ Object-Oriented Design and Programming ↓ Data Types and Sources ↓ Data Capture and…
*takes Tylenol* > be an electric engineering student > start quant trading *cracked af* > founded a quant firm in his 30’s > makes ¥100B trading with ai/ml *even more cracked with ai* > buys thousands of Nvdia GPUs CEO of DeepSeek everybody.
Build a Large Language Model from scratch! This repository contains the code examples for developing, pretraining, and finetuning a LLM from scratch. 100% Open Source
Getting a job is not fucking hard, you’re just lazy. This is how to get an interview for any job you want: 1. Discover role you want to apply for 2. Scrape MD or Senior Mgmt email from apollo or list kit 3. Email them and say: Hey Name, my name is X. I found your email in…
This is probably the worst job market for recent graduates and junior employees in a very long time If you have a good job currently, you should cherish it. You are one of the lucky ones
Literally all the resources you need to be a cracked ML/LLM engineer (coming from someone learning ML rn) >unsloth documentation >vLLM documentation (goated) >HF TEI docs (worth reading) >GPU glossary I wish I started with these a month ago. Expect much better ML content from…
An underrated course in Linear Algebra by Uni of Michigan 👇
Population vs Sample 📊 Population → the entire group you want to study. Sample → a small part of that group used to draw conclusions. 👉 Studying everyone = costly & slow. 👉 Studying a sample = efficient & practical. #DataScience #Statistics
This is literally everything you need to go from beginner to pro in AI
This prof from Yale literally shows how to think smarter than everyone around you
math/statistics ↓ python ↓ pandas ↓ numpy ↓ matplotlib ↓ mysql ↓ scikit learn ↓ xgboost ↓ pytorch ↓ transformers ↓ sbert ↓ fastapi ↓ dvc ↓ mlflow ↓ pyspark ↓ docker ↓ airflow ↓ ultralytics ↓ spacy ↓ opencv ↓ langchain ↓ qdrant congrats! ur now a full stack…
Descriptive vs Inferential Statistics Descriptive → Summarizes data (mean, median, charts, SD). Tells you what happened. Inferential → Uses sample data to make predictions about population. Tells you what it means. 👉 Descriptive = "What is." 👉 Inferential = "What could be."
You don’t need a PhD to learn AI, but you do need math & stats. They’re the language your models speak. Skip them, and you’re only memorizing spells without knowing the science. #Tech #AI #ML #DataScience
A 829 GB Mega Folder on Hacking ComTIA Hacking & Pentesting Linux Microsoft Programming Security Virtualization & more mega.nz/folder/1rBHzIy…
I interviewed over 50 back-end engineers in the last 2 years. I created a Notion based "Learn Backend Development Pack" that contains a learning path to become a backend dev based on free resources. Retweet and reply with "free" and I'll DM it to you. (need to follow)
Websites to create Resume/CV for free🤩👇🏻
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