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18s191

Course 18.S191 at MIT, fall 2020 - Introduction to computational thinking with Julia:

2022-machine-learning-specialization

advanced-deep-learning-with-keras

Advanced Deep Learning with Keras, published by Packt

aima-julia

Julia implementation of algorithms from Russell And Norvig's "Artificial Intelligence - A Modern Approach"

algorithm

My LeetCode Solutions with Explanation and Time Complexity Analysis

algorithmanddatastructure

互联网行业研发岗面试必备算法题配图解析及代码

algorithmsbypython

算法/数据结构/Python/剑指offer/机器学习/leetcode

all_leetcode_questions

All Leetcode questions in a single file

amazon-forecast-samples

Notebooks and examples on how to onboard and use various features of Amazon Forecast.

autoreply_sydneybot_reddit

An autoreply bot on Reddit powered by Sydney with customized settings

awesome-decision-tree-papers

A collection of research papers on decision, classification and regression trees with implementations.

awesome-production-machine-learning

A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning

bart

:exclamation: This is a read-only mirror of the CRAN R package repository. BART — Bayesian Additive Regression Trees

beamer-tips

beamerthemesaarland

Saarland Beamer Theme

bilibili_video_download

:rainbow:Bilibili_video_download-B站视频下载

bst

:exclamation: This is a read-only mirror of the CRAN R package repository. bst — Gradient Boosting

caret

caret (Classification And Regression Training) R package that contains misc functions for training and plotting classification and regression models

coding-problems

Solutions for various coding/algorithmic problems and many useful resources for learning algorithms and data structures

coding4interviews

Leetcode、剑指Offer——名企面试官精讲典型编程题

contextualbandits

Python implementations of contextual bandits algorithms

covid-mstate

cpp.primer-solution

This is a self-practice project.

cracking-the-data-science-interview

Resources for Oreilly's "Cracking the Data Science Interview" video series.

cxx.jl

The Julia C++ Interface

cxxwrap.jl

Package to make C++ libraries available in Julia

data-mining-notes

data-science-ipython-notebooks

Continually updated data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines. https://bit.ly/data-notes

data-scientists-guide-apache-spark

Best practices of using Spark for practicing data scientists in the context of a data scientist’s standard workflow.

dats_6103_introduction-to-data-mining_summer-ii_2016