Name		Name	Last commit message	Last commit date
Latest commit History 16 Commits
MachineLearningVisuals		MachineLearningVisuals
Mini Project sources		Mini Project sources
.DS_Store		.DS_Store
06-naiveBayes-example.pdf		06-naiveBayes-example.pdf
A Discriminative Feature Learning Approach for Deep Face Recognition.pdf		A Discriminative Feature Learning Approach for Deep Face Recognition.pdf
A Tutorial on Principal Components Analysis.pdf		A Tutorial on Principal Components Analysis.pdf
An introduction to ROC analysis.pdf		An introduction to ROC analysis.pdf
Applied Data Science.pdf		Applied Data Science.pdf
Artificial Inteligence.epub		Artificial Inteligence.epub
Benchmark Analysis of Representative Deep Neural Network Architectures.pdf		Benchmark Analysis of Representative Deep Neural Network Architectures.pdf
Best Practices for Machine Learning.pdf		Best Practices for Machine Learning.pdf
Chinese DL Notes.pdf		Chinese DL Notes.pdf
Comparison of Bagging, Boosting and Stacking Ensembles.pdf		Comparison of Bagging, Boosting and Stacking Ensembles.pdf
Data Warehouse.pdf		Data Warehouse.pdf
Decision Tree.pdf		Decision Tree.pdf
Deep Learning (Ian Goodfellow).pdf		Deep Learning (Ian Goodfellow).pdf
Deep Learning Models for Unsupervised and Transfer Learning.pdf		Deep Learning Models for Unsupervised and Transfer Learning.pdf
Deep Learning with R.pdf		Deep Learning with R.pdf
Deep Learning.pdf		Deep Learning.pdf
Deep Learning.pptx		Deep Learning.pptx
DevFestSiberia2016_VictorMaslov.ru.en.pdf		DevFestSiberia2016_VictorMaslov.ru.en.pdf
Discriminative Frequent Pattern Analysis for Effective Classification.pdf		Discriminative Frequent Pattern Analysis for Effective Classification.pdf
Effect coding versus dummy coding in analysis of data from factorial experiments.pdf		Effect coding versus dummy coding in analysis of data from factorial experiments.pdf
Grokking_Deep_Learning_v5_MEAP.pdf		Grokking_Deep_Learning_v5_MEAP.pdf
Instagram photos reveal predictive markers of depression.pdf		Instagram photos reveal predictive markers of depression.pdf
Introduction to Machine_Learning.pdf		Introduction to Machine_Learning.pdf
LICENSE		LICENSE
Language Processing and Python.pdf		Language Processing and Python.pdf
MINING HIGH-DIMENSIONAL DATA .pdf		MINING HIGH-DIMENSIONAL DATA .pdf
Machine Learning Algorithms.png		Machine Learning Algorithms.png
Machine Learning.pptx		Machine Learning.pptx
MachineLearning-Assignment-4-Solution.pdf		MachineLearning-Assignment-4-Solution.pdf
Murtaza Haider-Getting Started with Data Science_ Making Sense of Data with Analytics-IBM Press (2015).pdf		Murtaza Haider-Getting Started with Data Science_ Making Sense of Data with Analytics-IBM Press (2015).pdf
OpenFace.pdf		OpenFace.pdf
Predictive analytics and data mining - concepts and practice with RapidMiner.pdf		Predictive analytics and data mining - concepts and practice with RapidMiner.pdf
Python Machine Learning.pdf		Python Machine Learning.pdf
Recursive Partitioning Yale.pdf		Recursive Partitioning Yale.pdf
SENet.pdf		SENet.pdf
Squeezing Deep Learning Into Mobile Phones.pptx		Squeezing Deep Learning Into Mobile Phones.pptx
The Essential Guide to Training Data.pdf		The Essential Guide to Training Data.pdf
Tutorial6.pdf		Tutorial6.pdf
Understanding Random Forests.pdf		Understanding Random Forests.pdf
VGGFace1- Deep Face Recognition (VGG-Face).pdf		VGGFace1- Deep Face Recognition (VGG-Face).pdf
VGGFace2- A dataset for recognising faces across pose and age.pdf		VGGFace2- A dataset for recognising faces across pose and age.pdf
Version Space.pdf		Version Space.pdf
Visual Psychophysics for Making Face Recognition Algorithms More Explainable.pdf		Visual Psychophysics for Making Face Recognition Algorithms More Explainable.pdf
Visualizing and Understanding Convolutional Networks.pdf		Visualizing and Understanding Convolutional Networks.pdf
cheatsheet-machine-learning-tips-and-tricks.pdf		cheatsheet-machine-learning-tips-and-tricks.pdf
readme.md		readme.md

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AI-Reading-Materials

This repo contains some of the ML and DL related reading materials, research papers that I've read.

Feel free to discuss the contents of the papers together by opening an issue.

PRs are welcome if you wish to contribute to the reading shelf 🌟

Or you can fund my works 😁🎈

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