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Must Read Papers for Data Science, ML, and DL

Curated collection of Data Science, Machine Learning and Deep Learning papers, reviews and articles that are on must read list.

NOTE: :construction: in process of updating, let me know what additional papers, articles, blogs to add I will add them here.

How to use

:point_right: :star: this repo

Contributing

Maintenance

:point_down: READ THIS :point_down:

:1st_place_medal: - Read it first

:2nd_place_medal: - Read it second

:3rd_place_medal: - Read it third

Data Science

:bar_chart: Pre-processing & EDA

:1st_place_medal: :page_facing_up:Data preprocessing - Tidy data - by Hadley Wickham

:notebook: General DS

:1st_place_medal: :page_facing_up: Statistical Modeling: The Two Cultures - by Leo Breiman

:2nd_place_medal: :page_facing_up: A study in Rashomon curves and volumes: A new perspective on generalization and model simplicity in machine learning

:1st_place_medal: :page_facing_up: Frequentism and Bayesianism: A Python-driven Primer by Jake VanderPlas

Machine Learning

:dart: General ML

:1st_place_medal: :page_facing_up: Model Evaluation, Model Selection, and Algorithm Selection in Machine Learning - by Sebastian Raschka

:1st_place_medal: :page_facing_up: A Brief Introduction into Machine Learning - by Gunnar Ratsch

:3rd_place_medal: :page_facing_up: An Introduction to the Conjugate Gradient Method Without the Agonizing Pain - by Jonathan Richard Shewchuk

:3rd_place_medal: :page_facing_up: On Model Stability as a Function of Random Seed

:mag: Outlier/Anomaly detection

:1st_place_medal: :newspaper: Outlier Detection : A Survey

:rocket: Boosting

:2nd_place_medal: :page_facing_up: XGBoost: A Scalable Tree Boosting System

:2nd_place_medal: :page_facing_up: LightGBM: A Highly Efficient Gradient BoostingDecision Tree

:2nd_place_medal: :page_facing_up: AdaBoost and the Super Bowl of Classifiers - A Tutorial Introduction to Adaptive Boosting

:3rd_place_medal: :page_facing_up: Greedy Function Approximation: A Gradient Boosting Machine

:book: Unraveling Blackbox ML

:3rd_place_medal: :page_facing_up: Peeking Inside the Black Box: Visualizing Statistical Learning with Plots of Individual Conditional Expectation

:3rd_place_medal: :page_facing_up: Data Shapley: Equitable Valuation of Data for Machine Learning

:scissors: Dimensionality Reduction

:1st_place_medal: :page_facing_up: A Tutorial on Principal Component Analysis

:2nd_place_medal: :page_facing_up: How to Use t-SNE Effectively

:3rd_place_medal: :page_facing_up: Visualizing Data using t-SNE

:chart_with_upwards_trend: Optimization

:1st_place_medal: :page_facing_up: A Tutorial on Bayesian Optimization

:2nd_place_medal: :page_facing_up: Taking the Human Out of the Loop: A review of Bayesian Optimization

Famous Blogs

Sebastian Raschka Chip Huyen

:8ball: :crystal_ball: Recommenders

Surveys

:1st_place_medal: :page_facing_up: A Survey of Collaborative Filtering Techniques

:1st_place_medal: :page_facing_up: Collaborative Filtering Recommender Systems

:1st_place_medal: :page_facing_up: Deep Learning Based Recommender System: A Survey and New Perspectives

:1st_place_medal: :page_facing_up: :thinking: :star: Explainable Recommendation: A Survey and New Perspectives :star:

Case Studies

:2nd_place_medal: :page_facing_up: The Netflix Recommender System: Algorithms, Business Value,and Innovation

:2nd_place_medal: :page_facing_up: Two Decades of Recommender Systems at Amazon.com

:2nd_place_medal: :globe_with_meridians: How Does Spotify Know You So Well?

:point_right: More In-Depth study, :closed_book: Recommender Systems Handbook

Famous Deep Learning Blogs :cowboy_hat_face:

:globe_with_meridians: Stanford UFLDL Deep Learning Tutorial

:globe_with_meridians: Distill.pub

:globe_with_meridians: Colah's Blog

:globe_with_meridians: Andrej Karpathy

:globe_with_meridians: Zack Lipton

:globe_with_meridians: Sebastian Ruder

:globe_with_meridians: Jay Alammar

:books: Neural Networks and Deep Learning Neural Networks

:star: :1st_place_medal: :newspaper: The Matrix Calculus You Need For Deep Learning - Terence Parr and Jeremy Howard :star:

:1st_place_medal: :newspaper: Deep learning -Yann LeCun, Yoshua Bengio & Geoffrey Hinton

:1st_place_medal: :page_facing_up: Generalization in Deep Learning

:1st_place_medal: :page_facing_up: Topology of Learning in Artificial Neural Networks

:1st_place_medal: :page_facing_up: Dropout: A Simple Way to Prevent Neural Networks from Overfitting

:2nd_place_medal: :page_facing_up: Polynomial Regression As an Alternative to Neural Nets

:2nd_place_medal: :globe_with_meridians: The Neural Network Zoo

:2nd_place_medal: :globe_with_meridians: Image Completion with Deep Learning in TensorFlow

:2nd_place_medal: :page_facing_up: Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

:3rd_place_medal: :page_facing_up: A systematic study of the class imbalance problem in convolutional neural networks

:3rd_place_medal: :page_facing_up: All Neural Networks are Created Equal

:3rd_place_medal: :page_facing_up: Adam: A Method for Stochastic Optimization

:3rd_place_medal: :page_facing_up: AutoML: A Survey of the State-of-the-Art

:framed_picture: CNNs

:1st_place_medal: :page_facing_up: Visualizing and Understanding Convolutional Networks -by Andrej Karpathy Justin Johnson Li Fei-Fei

:2nd_place_medal: :page_facing_up: Deep Residual Learning for Image Recognition

:2nd_place_medal: :page_facing_up:AlexNet-ImageNet Classification with Deep Convolutional Neural Networks

:2nd_place_medal: :page_facing_up:VGG Net-VERY DEEP CONVOLUTIONAL NETWORKS FOR LARGE-SCALE IMAGE RECOGNITION

:3rd_place_medal: :page_facing_up: A Mathematical Theory of Deep Convolutional Neural Networks for Feature Extraction

:3rd_place_medal: :page_facing_up: Large-scale Video Classification with Convolutional Neural Networks

:3rd_place_medal: :page_facing_up: Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering

:black_circle: CapsNet :trident:

:1st_place_medal: :page_facing_up: Dynamic Routing Between Capsules

:national_park: :speech_balloon: Image Captioning

:1st_place_medal: :page_facing_up: Show and Tell: A Neural Image Caption Generator

:2nd_place_medal: :page_facing_up: Neural Machine Translation by Jointly Learning to Align and Translate

:2nd_place_medal: :page_facing_up: StyleNet: Generating Attractive Visual Captions with Styles

:2nd_place_medal: :page_facing_up: Show, Attend and Tell: Neural Image Caption Generation with Visual Attention

:2nd_place_medal: :page_facing_up: Where to put the Image in an Image Caption Generator

:2nd_place_medal: :page_facing_up: Dank Learning: Generating Memes Using Deep Neural Networks

:car: :walking_man: Object Detection :eagle: :football:

:2nd_place_medal: :page_facing_up:ResNet-Deep Residual Learning for Image Recognition

:2nd_place_medal: :page_facing_up: YOLO-You Only Look Once: Unified, Real-Time Object Detection

:2nd_place_medal: :page_facing_up: Microsoft COCO: Common Objects in Context

:2nd_place_medal: :page_facing_up: (R-CNN) Rich feature hierarchies for accurate object detection and semantic segmentation

:2nd_place_medal: :page_facing_up: Fast R-CNN

:2nd_place_medal: :page_facing_up: Faster R-CNN

:2nd_place_medal: :page_facing_up: Mask R-CNN

:car: :walking_man: :couple: Pose Detection :runner: :dancer:

:2nd_place_medal: :page_facing_up: DensePose: Dense Human Pose Estimation In The Wild

:2nd_place_medal: :page_facing_up: Parsing R-CNN for Instance-Level Human Analysis

:abcd: :symbols: Deep NLP :currency_exchange: :1234:

:1st_place_medal: :page_facing_up: A Primer on Neural Network Models for Natural Language Processing

:1st_place_medal: :page_facing_up: Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling

:1st_place_medal: :page_facing_up: On the Properties of Neural Machine Translation: Encoder–Decoder Approaches

:1st_place_medal: :page_facing_up: LSTM: A Search Space Odyssey - by Klaus Greff et al.

:1st_place_medal: :page_facing_up: A Critical Review of Recurrent Neural Networksfor Sequence Learning

:1st_place_medal: :page_facing_up: Visualizing and Understanding Recurrent Networks

:star: :1st_place_medal: :page_facing_up: Attention Is All You Need :star:

:1st_place_medal: :page_facing_up: An Empirical Exploration of Recurrent Network Architectures

:1st_place_medal: :page_facing_up: Open AI (GPT-2) Language Models are Unsupervised Multitask Learners

:1st_place_medal: :page_facing_up: BERT: Pre-training of Deep Bidirectional Transformers forLanguage Understanding

:3rd_place_medal: :page_facing_up: Parameter-Efficient Transfer Learning for NLP

:3rd_place_medal: :page_facing_up: A Sensitivity Analysis of (and Practitioners’ Guide to) ConvolutionalNeural Networks for Sentence Classification

:3rd_place_medal: :page_facing_up: A Survey on Recent Advances in Named Entity Recognition from Deep Learning models

:3rd_place_medal: :page_facing_up: Convolutional Neural Networks for Sentence Classification

:3rd_place_medal: :page_facing_up: Pervasive Attention: 2D Convolutional Neural Networks for Sequence-to-Sequence Prediction

:3rd_place_medal: :page_facing_up: Single Headed Attention RNN: Stop Thinking With Your Head

:alien: GANs

:1st_place_medal: :page_facing_up: Generative Adversarial Nets - Goodfellow et al.

:books: GAN Rabbit Hole -> GAN Papers

:o::heavy_minus_sign::o: GNNs (Graph Neural Networks)

:3rd_place_medal: :page_facing_up: A Comprehensive Survey on Graph Neural Networks

:man_health_worker: :syringe: Medical AI :pill: :microscope:

Machine learning classifiers and fMRI: a tutorial overview - by Francisco et al.

:point_down: Cool Stuff :point_down:

:loud_sound: :page_facing_up: SoundNet: Learning Sound Representations from Unlabeled Video

:art: :page_facing_up: CAN: Creative Adversarial NetworksGenerating “Art” by Learning About Styles andDeviating from Style Norms

:art: :page_facing_up: Deep Painterly Harmonization

:man_dancing: :dancer: :page_facing_up: Everybody Dance Now

:soccer: Soccer on Your Tabletop

:blonde_woman: :haircut_woman: :page_facing_up: SC-FEGAN: Face Editing Generative Adversarial Network with User's Sketch and Color

:camera_flash: :page_facing_up: Handheld Mobile Photography in Very Low Light

:japanese_castle: :mosque: :page_facing_up: Learning Deep Features for Scene Recognitionusing Places Database

:bullettrain_front: :bullettrain_side: :page_facing_up: High-Speed Tracking withKernelized Correlation Filters

:clapper: :page_facing_up: Recent progress in semantic image segmentation

Rabbit hole -> :loud_sound: :globe_with_meridians: Analytics Vidhya Top 10 Audio Processing Tasks and their papers

:blonde_man: -> :older_man: :page_facing_up: :page_facing_up: Face Aging With Condintional GANS

:blonde_man: -> :older_man: :page_facing_up: :page_facing_up: Dual Conditional GANs for Face Aging and Rejuvenation

:balance_scale: :page_facing_up: BAGAN: Data Augmentation with Balancing GAN

labml.ai Annotated PyTorch Paper Implementations

:newspaper: Cap Stone Projects :newspaper:

8 Awesome Data Science Capstone Projects

10 Powerful Applications of Linear Algebra in Data Science

Top 5 Interesting Applications of GANs

Deep Learning Applications a beginner can build in minutes

CHANGELOG

2019-10-28 Started must-read-papers-for-ml repo

2019-10-29 Added analytics vidhya use case studies article links

2019-10-30 Added Outlier/Anomaly detection paper, separated Boosting, CNN, Object Detection, NLP papers, and added Image captioning papers

2019-10-31 Added Famous Blogs from Deep and Machine Learning Researchers

2019-11-1 Fixed markdown issues, added contribution guideline

2019-11-20 Added Recommender Surveys, and Papers

2019-12-12 Added R-CNN variants, PoseNets, GNNs

2020-02-23 Added GRU paper