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120-data-science-interview-questions

Answers to 120 commonly asked data science interview questions.

30-days-of-react

30 Days of React challenge is a step by step guide to learn React in 30 days. It requires HTML, CSS, and JavaScript knowledge. You should be comfortable with JavaScript before you start to React. If you are not comfortable with JavaScript check out 30DaysOfJavaScript. This is a continuation of 30 Days Of JS. This challenge may take more than 100 days, follow your own pace.

500-ai-machine-learning-deep-learning-computer-vision-nlp-projects-with-code

500 AI Machine learning Deep learning Computer vision NLP Projects with code

awesome-deep-learning

A curated list of awesome Deep Learning tutorials, projects and communities.

cpp-primer-

Solutions to all exercises of C++ Primer Plus, 6th ed., by Stephen Prata.

deeplearning-500-questions

深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系[email protected] 版权所有，违权必究 Tan 2018.06

fluent_python

Example code for Fluent Python, 2nd edition (O'Reilly 2022)

full-blockchain-solidity-course-js

Learn Blockchain, Solidity, and Full Stack Web3 Development with Javascript

grokking-the-coding-interview-patterns-for-coding-questions

hpc_hw4

machine-learning-from-scratch

Implementation of popular ML algorithms from scratch

ml-from-scratch

Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.

mlquestions

Machine Learning and Computer Vision Engineer - Technical Interview Questions

numpy-ml

Machine learning, in numpy

nyu-devops-concepts

Documentation supporting the NYU DevOps course.

python_mastery_code_snippets

pytorch-beginner

pytorch tutorial for beginners

pytorch-deep-learning

Deep Learning (with PyTorch)

quant-notes

Quantitative Interview Preparation Guide, updated version here ==>

statsintro_python

Python modules and IPython Notebooks, for the book "Introduction to Statistics With Python"

the-craft-of-selfteaching

One has no future if one couldn't teach themself.

xgboost

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow