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100-days-of-ml-code

100 Days of ML Coding

120-ds-interview-questions

My Answer to 120 Data Science Interview Questions

ai-expert-roadmap

Roadmap to becoming an Artificial Intelligence Expert in 2021

applied-ml

📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

awesome-atmos

A curated list of awesome Python libraries, software and resources in Atmosphere, Environment and Machine Learning

awesome-database-learning

A list of learning materials to understand databases internals

awesome-full-stack-machine-courses

Curated list of publicly accessible machine learning engineering courses from CalTech, Columbia, Berkeley, MIT, and Stanford.

awesome-llms-fine-tuning

Explore a comprehensive collection of resources, tutorials, papers, tools, and best practices for fine-tuning Large Language Models (LLMs). Perfect for ML practitioners and researchers!

breadth-first-search

Implement the graph search version of breadth-first search in Java

chatgpt-prompt-engineering

Jupyter code notebooks of "ChatGPT Prompt Engineering for Developers" by DeepLearning.AI and OpenAI.

cira_ml_short_course

Notebooks for CIRA (Cooperative Institute for Research in the Atmosphere) machine-learning short course.

cookbook

The Data Engineering Cookbook

coursera-applied-data-science-with-python

This repository contains the materials to "Applied Data Science with Python", a specialization provided by University of Michigan through Coursera.

coursera-deep-learning-specialization

programming assignments from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iv) Convolutional Neural Network; (v) Sequence Models

coursera-learn-sql-basics-for-data-science

This repository contains the materials to "Learn SQL Basics for Data Science", a specialization provided by University of California, Davis through Coursera.

coursera-machine-learning-stanford

This repository contains MATLAB Implementation of certain programming assignments of Andrew Ng’s Machine Learning Course on Coursera, created by Stanford University.

courseralectures

Lecture Materials for Coursera Courses by Roger Peng

courses

Course materials for the Data Science Specialization: https://www.coursera.org/specialization/jhudatascience/1

cs-notes

:books: 技术面试必备基础知识、Leetcode、计算机操作系统、计算机网络、系统设计

data-cleaning-tool

A prototype built in Python to prepare data ready for visualisation

data-engineer-roadmap

Roadmap to becoming a data engineer in 2021

data-engineering-zoomcamp

Free Data Engineering course!

data-science-ipython-notebooks

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

dbt_demo1

deep-learning-with-python-notebooks

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

excel_practice

This is an excel practice which contains vlookup, countif, matching

freeml

A List of Data Science/Machine Learning Resources (Mostly Free)

go

The Open Source Data Science Masters

hackerrank_solutions

317 efficient solutions to HackerRank problems

interview

Interview = 简历指南 + LeetCode + Kaggle