mld's starred repositories

Data-Science-ML-Full-Stack-2022

Everything you need to know for data science.

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God-Level-AI

A collection of scientific methods, processes, algorithms, and systems to build stories & models.

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sg-tech-list

:scroll: List of notable tech companies in Singapore

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TOEFL_MATERIAL

Download the TOEFL Material from here

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de4ml

Supporting materials/code examples for my course in data engineering for machine learning.

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Awesome-Diffusion-Models

A collection of resources and papers on Diffusion Models

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plotly-resampler

Visualize large time series data with plotly.py

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ivy

The Unified AI Framework

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domain-driven-hexagon

Learn Domain-Driven Design, software architecture, design patterns, best practices. Code examples included

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awesome-guidelines

A curated list of high quality coding style conventions and standards.

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every-programmer-should-know

A collection of (mostly) technical things every software developer should know about

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30-seconds-of-code

Short code snippets for all your development needs

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professional-programming

A collection of learning resources for curious software engineers

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aws-machine-learning-university-dte

Machine Learning University: Decision Trees and Ensemble Methods

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aws-machine-learning-university-accelerated-tab

Machine Learning University: Accelerated Tabular Data Class

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aws-mlu-explain

Visual, Interactive Articles About Machine Learning: https://mlu-explain.github.io/

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sklearn_pycon2015

Materials for my Pycon 2015 scikit-learn tutorial.

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scikit-learn-videos

Jupyter notebooks from the scikit-learn video series

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Data-Science-Interview-Questions-Answers

Curated list of data science interview questions and answers

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awesome-ml-for-cybersecurity

:octocat: Machine Learning for Cyber Security

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qlib

Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas to implementing productions. Qlib supports diverse machine learning modeling paradigms. including supervised learning, market dynamics modeling, and RL.

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system-design

Learn how to design systems at scale and prepare for system design interviews

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tricking-data-science

A book of subtle code tricks and gem resources for all things data, machine learning and deep learning.

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FREE_7773

Materials for my 2021 NYU class on NLP and ML Systems (Master of Engineering).

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skorch

A scikit-learn compatible neural network library that wraps PyTorch

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dataviz

A book covering the fundamentals of data visualization

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microprediction

If you can measure it, consider it predicted

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front-end-interview-handbook

⚡️ Front End interview preparation materials for busy engineers

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tech-interview-handbook

💯 Curated interview preparation materials for busy engineers

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