ANUBHAV NEHRU's starred repositories

GPTInterviewer

GPT Interviewer - Practice interview with AI interviewer based on job descriptions and resume

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gorilla

Gorilla: Training and Evaluating LLMs for Function Calls (Tool Calls)

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vision-transformer

Vision Transformer explanation and implementation with PyTorch

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CrackingMachineLearningInterview

A repository to prepare you for your machine learning interview, involving most of the questions asked by all the tech giants and local companies. Do this to Ace your Machine Learning Engineer Interviews

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Machine-Learning-Interview-Questions

This repository is regarding important questions asked in Machine Learning Engineer Interviews.

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machine-learning-interview

Machine Learning Interviews from FAANG, Snapchat, LinkedIn. I have offers from Snapchat, Coupang, Stitchfix etc. Blog: mlengineer.io.

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MLQuestions

Machine Learning and Computer Vision Engineer - Technical Interview Questions

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Data-Science-Interview-Questions-Answers

Curated list of data science interview questions and answers

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tldw

Too Long, Didn't Watch: End-to-End Rolling Summarizer of Long Videos

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Awesome-LLM

Awesome-LLM: a curated list of Large Language Model

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llm-course

Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.

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medium

Code repository for my medium articles

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data-science-blogs

A curated list of data science blogs

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innvestigate

A toolbox to iNNvestigate neural networks' predictions!

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ai_all_resources

A curated list of Best Artificial Intelligence Resources

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awesome-mlops

A curated list of references for MLOps

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mml-book.github.io

Companion webpage to the book "Mathematics For Machine Learning"

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MML-Book

Code / solutions for Mathematics for Machine Learning (MML Book)

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python-metar

a python package that parses coded METAR weather reports.

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handson-ml

⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 instead.

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Nanodegrees

Nanodegree programs https://www.udacity.com/nanodegree

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pydata-book

Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media

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