Ionel Miu's repositories
Papers-Literature-ML-DL-RL-AI
Highly cited and useful papers related to machine learning, deep learning, AI, game theory, reinforcement learning
100-nlp-papers
100 Must-Read NLP Papers
aurioTouch2.0-Swift
A translation of Apple's sample code aurioTouch (Version 5.0) into Swift (Sorry for including mismatching version number)
awesome-distributed-systems
A curated list to learn about distributed systems
channel-capacity-estimator
Tool for channel capacity estimation
cheatsheets
RStudio Cheat Sheets
data-analysis-for-social-scientists-mitx
R scripts written for MIT's Data Analysis for Social Scientists course offered on edX.
datashader
Turns even the largest data into images, accurately.
free-programming-books
:books: Freely available programming books
Machine-Learning-Tutorials
machine learning and deep learning tutorials, articles and other resources
MAT331
I designed this statistical modeling course for Stony Brook University. All course materials - python codes, experiments, results, solutions can be found here
MITx_14.310x_Data_Analysis_for_Social_Scientist_Fall_2020
This course introduces methods for harnessing data to answer questions of cultural, social, economic, and policy interest. We will start with essential notions of probability and statistics. We will proceed to cover techniques in modern data analysis: regression and econometrics, design of experiments, randomized control trials (and A/B testing), machine learning, data visualization. We will illustrate these concepts with applications drawn from real world examples and frontier research. Finally, we will provide instruction on the use of the statistical package R, and opportunities for students to perform self-directed empirical analyses. Students taking the graduate version will complete additional assignments. No prior preparation in probability and statistics is required, but familiarity with basic algebra and calculus is assumed.
MITxMachineLearningClass
EdX course from MIT on machine learning 6.86x
mlrefined
Jupyter notebooks, Python and MATLAB code examples, and demos from the textbook "Machine Learning Refined" (Cambridge University Press). See our blog https://jermwatt.github.io/mlrefined/index.html for interactive versions of many of the notebooks in this repo.
NaiveBayesClassifier
Implementation of Normal and Bernoulli Naive Bayes Classifier, test with pima-indian-diabetes and MNIST dataset and comparison with sklearn Naive Bayes implementation
openqml
QML and NISQ algorithms
Python-3-Object-Oriented-Programming-Third-Edition
Python 3 Object-Oriented Programming – Third Edition, published by Packt
PythonDataScienceHandbook
Python Data Science Handbook: full text in Jupyter Notebooks
Quantum-Computing
QC Study Group Github Repository
R-Talks
R Presentations, including Kansas City R Users Group
Skin_lesion_analysis_for_melanoma_detection
This is a research project for using instance segmentation networks for cancer detection
Statistics-Books
"If your experiment needs a statistician, you need a better experiment." ― Ernest Rutherford
ventilator
Low-Cost Open Source Ventilator or PAPR