awesome-datascience
:memo: An awesome Data Science repository to learn and apply for real world problems.
https://github.com/academic/awesome-datascience
Last synced: about 13 hours ago
JSON representation
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The Data Science Toolbox
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Algorithms
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- Stacking
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
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Deep Learning Packages
- Sonnet
- TRFL
- TensorLight
- Keras
- altair
- addepar
- amcharts
- anychart
- bokeh
- Comet
- slemma
- d3plus
- Data-Driven Documents(D3js)
- dygraphs
- ECharts
- exhibit
- gephi
- ggplot2
- Glue
- Google Chart Gallery
- highcarts
- import.io
- jqplot
- Matplotlib
- nvd3
- Openrefine
- plot.ly
- raw
- Seaborn
- techanjs
- Timeline
- variancecharts
- vida
- Wrangler
- r2d3
- NetworkX
- Redash
- C3
- geomap
- TensorLight
- Sonnet
- TRFL
- Keras
- plot.ly
- PyTorch
- torchvision
- torchtext
- torchaudio
- ignite
- PyTorchNet
- PyToune
- skorch
- PyVarInf
- pytorch_geometric
- GPyTorch
- pyro
- Catalyst
- pytorch_tabular
- Yolov3
- Yolov5
- Yolov8
- TensorFlow
- TensorLayer
- TFLearn
- tensorpack
- Polyaxon
- NeuPy
- tfdeploy
- TensorFlow Fold
- tensorlm
- Mesh TensorFlow
- Ludwig
- TF-Agents
- TensorForce
- keras-contrib
- Hyperas
- Elephas
- Hera
- Spektral
- qkeras
- keras-rl
- Talos
- cartodb
- Cube
- Resseract Lite
- vizzu
- Netron
- TRFL
- tensorflow-upstream
- TensorLight
- Sonnet
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Comparison
- Regression
- Stacking
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- datacompy - DataComPy is a package to compare two Pandas DataFrames.
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- C4.5
- Conditional Random Field (CRF)
- Latent Dirichlet Allocation (LDA)
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- SVM (Support Vector Machine)
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- Linear Regression
- Ordinary Least Squares
- Logistic Regression
- Stepwise Regression
- Multivariate Adaptive Regression Splines
- Softmax Regression
- Locally Estimated Scatterplot Smoothing
- Decision Trees
- ID3 algorithm
- Ensemble Learning
- Boosting
- Bagging
- Random Forest
- AdaBoost
- Fuzzy clustering
- Mixture models
- Dimension Reduction
- Neural Networks
- Adaptive resonance theory
- Hidden Markov Models (HMM)
- Q Learning
- SARSA (State-Action-Reward-State-Action) algorithm
- Temporal difference learning
- k-Means
- Apriori
- EM (Expectation-Maximization)
- PageRank
- Naive Bayes
- CART (Classification and Regression Trees)
- Multilayer Perceptron
- Convolutional Neural Network (CNN)
- Recurrent Neural Network (RNN)
- Boltzmann Machines
- Autoencoder
- Generative Adversarial Network (GAN)
- Transformer
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
- Heuristic approaches
- Conditional Random Field (CRF)
- Density-based clustering
- Self-Organized Maps
- KNN (K-Nearest Neighbors)
- ML System Designs)
- Conditional Random Field (CRF)
- Conditional Random Field (CRF)
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General Machine Learning Packages
- scikit-learn
- Shogun
- hyperlearn
- scikit-survival
- hyperlearn
- scikit-multilearn
- sklearn-expertsys
- scikit-feature
- scikit-rebate
- seqlearn
- sklearn-bayes
- sklearn-crfsuite
- sklearn-deap
- sigopt_sklearn
- sklearn-evaluation
- scikit-image
- scikit-opt
- scikit-posthocs
- pystruct
- xLearn
- cuML
- causalml
- mlpack
- MLxtend
- modAL
- Sparkit-learn
- dlib
- imodels
- RuleFit
- pyGAM
- Deepchecks
- XGBoost
- LightGBM
- CatBoost
- interpretable
- hyperlearn
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Miscellaneous Tools
- Data Science Lifecycle Template Repo
- Neptune.ai - friendly platform supporting data scientists in creating and sharing machine learning models. Neptune facilitates teamwork, infrastructure management, models comparison and reproducibility. |
- Datalab from Google
- Hortonworks Sandbox
- R
- Tidyverse
- RStudio
- Python - Pandas - Anaconda - ready Python distribution for large-scale data processing, predictive analytics, and scientific computing |
- Scikit-Learn
- NumPy - dimensional arrays and matrices and includes an assortment of high-level mathematical functions to operate on these arrays. |
- Vaex
- SciPy
- Data Science Toolbox
- Datadog - scale data science. |
- Variance
- Kite Development Kit
- Domino Data Labs
- Apache Flink - purpose data processing. |
- Apache Hama - Level open source project, allowing you to do advanced analytics beyond MapReduce. |
- Weka
- Octave - level interpreted language, primarily intended for numerical computations.(Free Matlab) |
- Apache Spark - fast cluster computing |
- Data Mechanics - friendly and cost-effective. |
- Caffe
- Torch
- Aerosolve
- Datawrapper
- Tensor Flow
- Natural Language Toolkit
- nlp-toolkit for node.js
- Julia - level, high-performance dynamic programming language for technical computing |
- Apache Zeppelin - based notebook that enables data-driven, interactive data analytics and collaborative documents with SQL, Scala and more |
- LightTag
- UBIAI - to-use text annotation tool for teams with most comprehensive auto-annotation features. Supports NER, relations and document classification as well as OCR annotation for invoice labeling |
- AWS Data Wrangler - source Python package that extends the power of Pandas library to AWS connecting DataFrames and AWS data related services (Amazon Redshift, AWS Glue, Amazon Athena, Amazon EMR, etc). |
- Amazon Rekognition
- Amazon Textract
- Amazon Lookout for Vision
- Amazon CodeGuru - powered recommendations.|
- Dask
- Statsmodels - based inferential statistics, hypothesis testing and regression framework |
- Gensim - source library for topic modeling of natural language text |
- spaCy
- DAGsHub
- Deepnote - compatible, with real-time collaboration and running in the cloud. |
- Valohai
- PyMC3
- PyStan
- hmmlearn
- Nimblebox - stack MLOps platform designed to help data scientists and machine learning practitioners around the world discover, create, and launch multi-cloud apps from their web browser. |
- Explore Data Science Libraries
- MLflow
- AutoGluon - series, and multi-modal data |
- Arize AI - causing issues such as data quality and performance drift. |
- Aureo.io - code platform that focuses on building artificial intelligence. It provides users with the capability to create pipelines, automations and integrate them with artificial intelligence models – all with their basic data. |
- ERD Lab
- Arize-Phoenix - uncover insights, surface problems, monitor, and fine tune your models. |
- Synthical - powered collaborative environment for research. Find relevant papers, create collections to manage bibliography, and summarize content — all in one place |
- AWS Data Wrangler - source Python package that extends the power of Pandas library to AWS connecting DataFrames and AWS data related services (Amazon Redshift, AWS Glue, Amazon Athena, Amazon EMR, etc). |
- AutoGluon - series, and multi-modal data |
- Neptune.ai - friendly platform supporting data scientists in creating and sharing machine learning models. Neptune facilitates teamwork, infrastructure management, models comparison and reproducibility. |
- Synthical - powered collaborative environment for research. Find relevant papers, create collections to manage bibliography, and summarize content — all in one place |
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Training Resources
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Free Courses
- Data Scientist with R
- Data Scientist with R
- Data Scientist with Python
- Genetic Algorithms OCW Course
- Convex Optimization - Convex Optimization (basics of convex analysis; least-squares, linear and quadratic programs, semidefinite programming, minimax, extremal volume, and other problems; optimality conditions, duality theory...)
- Skillcombo - Data Science - 1000+ free online Data Science courses
- Learning from Data - Introduction to machine learning covering basic theory, algorithms and applications
- Kaggle - Learn about Data Science, Machine Learning, Python etc
- ML Observability Fundamentals - Learn how to monitor and root-cause production ML issues.
- Weights & Biases Effective MLOps: Model Development - Free Course and Certification for building an end-to-end machine using W&B
- Python for Data Science by Scaler - This course is designed to empower beginners with the essential skills to excel in today's data-driven world. The comprehensive curriculum will give you a solid foundation in statistics, programming, data visualization, and machine learning.
- MLSys-NYU-2022 - Slides, scripts and materials for the Machine Learning in Finance course at NYU Tandon, 2022.
- Data Scientist with Python
- Prompt Engineering for Vision Models - Learn to prompt cutting-edge computer vision models with natural language, coordinate points, bounding boxes, segmentation masks, and even other images in this free course from DeepLearning.AI.
- Python for Machine Learning - Start your journey to machine learning with Python, one of the most powerful programming languages.
- AI Expert Roadmap - Roadmap to becoming an Artificial Intelligence Expert
- Hands-on Train and Deploy ML - A hands-on course to train and deploy a serverless API that predicts crypto prices.
- LLMOps: Building Real-World Applications With Large Language Models - Learn to build modern software with LLMs using the newest tools and techniques in the field.
- Data Science Course By IBM - Free resources and learn what data science is and how it’s used in different industries.
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Tutorials
- 1000 Data Science Projects
- How To Label Data
- Your Guide to Latent Dirichlet Allocation
- Over 1000 Data Science Online Courses at Classpert Online Search Engine
- Python for Data Science: A Beginner’s Guide
- 12 free Data Science projects to practice Python and Pandas
- #tidytuesday
- Data science your way
- PySpark Cheatsheet
- Tutorials of source code from the book Genetic Algorithms with Python by Clinton Sheppard
- Tutorials to get started on signal processing for machine learning
- Minimum Viable Study Plan for Machine Learning Interviews
- Machine Learning, Data Science and Deep Learning with Python
- Best CV/Resume for Data Science Freshers
- Understand Data Science Course in Java
- Realtime deployment - series model deployment.
- 1000 Data Science Projects
- Understand and Know Machine Learning Engineering by Building Solid Projects
- Data Analytics Interview Questions (Beginner to Advanced)
- Top 100+ Data Science Interview Questions and Answers
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MOOC's
- Coursera Introduction to Data Science
- Data Science - 9 Steps Courses, A Specialization on Coursera
- Data Mining - 5 Steps Courses, A Specialization on Coursera
- Machine Learning – 5 Steps Courses, A Specialization on Coursera
- OpenIntro
- CS 171 Visualization
- Process Mining: Data science in Action
- Oxford Deep Learning
- Oxford Deep Learning - video
- Oxford Machine Learning
- UBC Machine Learning - video
- Coursera Big Data Specialization
- Statistical Thinking for Data Science and Analytics by Edx
- Cognitive Class AI by IBM
- Udacity - Deep Learning
- Keras in Motion
- Microsoft Professional Program for Data Science
- COMP3222/COMP6246 - Machine Learning Technologies
- CS 231 - Convolutional Neural Networks for Visual Recognition
- Coursera Tensorflow in practice
- Coursera Deep Learning Specialization
- 365 Data Science Course
- Coursera Natural Language Processing Specialization
- Coursera GAN Specialization
- Codecademy's Data Science
- Linear Algebra - Linear Algebra course by Gilbert Strang
- A 2020 Vision of Linear Algebra (G. Strang)
- Python for Data Science Foundation Course
- Data Science: Statistics & Machine Learning
- Machine Learning Engineering for Production (MLOps)
- Recommender Systems Specialization from University of Minnesota
- Stanford Artificial Intelligence Professional Program
- Data Scientist with Python
- Programming with Julia
- Scaler Data Science & Machine Learning Program
- CS 109 Data Science
- Data Science Specialization
- Oxford Deep Learning - video
- Data Science Skill Tree
- Python for Data Science Foundation Course
- Data Science for Beginners - Learn with AI tutor
- Machine Learning for Beginners - Learn with AI tutor
- Data Scientist with Python
- Linear Algebra - Linear Algebra course by Gilbert Strang
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Intensive Programs
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Colleges
- Data Science Degree @ Berkeley
- Data Science Degree @ UVA
- Data Science Degree @ Wisconsin
- BS in Data Science & Applications
- MS in Computer Information Systems @ Boston University
- MS in Applied Data Science @ Syracuse
- M.S. Management & Data Science @ Leuphana
- Master of Data Science @ Melbourne University
- Msc in Data Science @ The University of Edinburgh
- Master of Management Analytics @ Queen's University
- Master of Data Science @ Illinois Institute of Technology
- Master of Applied Data Science @ The University of Michigan
- Master Data Science and Artificial Intelligence @ Eindhoven University of Technology
- Master's Degree in Data Science and Computer Engineering @ University of Granada
- A list of colleges and universities offering degrees in data science.
- Msc in Data Science @ The University of Edinburgh
- Master of Applied Data Science @ The University of Michigan
- Data Science Degree @ Wisconsin
- Master Data Science and Artificial Intelligence @ Eindhoven University of Technology
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Literature and Media
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Journals, Publications and Magazines
- Towards Data Science Genetic Algorithm Topic - Genetic Algorithm related Publications towards Data Science
- ICML - International Conference on Machine Learning
- GECCO - The Genetic and Evolutionary Computation Conference (GECCO)
- epjdatascience
- Journal of Data Science - an international journal devoted to applications of statistical methods at large
- Big Data Research
- Journal of Big Data
- Big Data & Society
- Data Science Journal
- datatau.com/news - Like Hacker News, but for data
- Data Science Trello Board
- Medium Data Science Topic - Data Science related publications on medium
- Towards Data Science Genetic Algorithm Topic - Genetic Algorithm related Publications towards Data Science
- all AI news - The AI/ML/Big Data news aggregator platform
- Towards Data Science Genetic Algorithm Topic - Genetic Algorithm related Publications towards Data Science
- Towards Data Science Genetic Algorithm Topic - Genetic Algorithm related Publications towards Data Science
- Towards Data Science Genetic Algorithm Topic - Genetic Algorithm related Publications towards Data Science
- Towards Data Science Genetic Algorithm Topic - Genetic Algorithm related Publications towards Data Science
- Towards Data Science Genetic Algorithm Topic - Genetic Algorithm related Publications towards Data Science
- Towards Data Science Genetic Algorithm Topic - Genetic Algorithm related Publications towards Data Science
- Towards Data Science Genetic Algorithm Topic - Genetic Algorithm related Publications towards Data Science
- Towards Data Science Genetic Algorithm Topic - Genetic Algorithm related Publications towards Data Science
- Towards Data Science Genetic Algorithm Topic - Genetic Algorithm related Publications towards Data Science
- Towards Data Science Genetic Algorithm Topic - Genetic Algorithm related Publications towards Data Science
- Towards Data Science Genetic Algorithm Topic - Genetic Algorithm related Publications towards Data Science
- Towards Data Science Genetic Algorithm Topic - Genetic Algorithm related Publications towards Data Science
- Towards Data Science Genetic Algorithm Topic - Genetic Algorithm related Publications towards Data Science
- Towards Data Science Genetic Algorithm Topic - Genetic Algorithm related Publications towards Data Science
- Towards Data Science Genetic Algorithm Topic - Genetic Algorithm related Publications towards Data Science
- Towards Data Science Genetic Algorithm Topic - Genetic Algorithm related Publications towards Data Science
- Towards Data Science Genetic Algorithm Topic - Genetic Algorithm related Publications towards Data Science
- Towards Data Science Genetic Algorithm Topic - Genetic Algorithm related Publications towards Data Science
- Towards Data Science Genetic Algorithm Topic - Genetic Algorithm related Publications towards Data Science
- Towards Data Science Genetic Algorithm Topic - Genetic Algorithm related Publications towards Data Science
- Towards Data Science Genetic Algorithm Topic - Genetic Algorithm related Publications towards Data Science
- Towards Data Science Genetic Algorithm Topic - Genetic Algorithm related Publications towards Data Science
- Towards Data Science Genetic Algorithm Topic - Genetic Algorithm related Publications towards Data Science
- Towards Data Science Genetic Algorithm Topic - Genetic Algorithm related Publications towards Data Science
- Towards Data Science Genetic Algorithm Topic - Genetic Algorithm related Publications towards Data Science
- Towards Data Science Genetic Algorithm Topic - Genetic Algorithm related Publications towards Data Science
- Towards Data Science Genetic Algorithm Topic - Genetic Algorithm related Publications towards Data Science
- Towards Data Science Genetic Algorithm Topic - Genetic Algorithm related Publications towards Data Science
- Towards Data Science Genetic Algorithm Topic - Genetic Algorithm related Publications towards Data Science
- Towards Data Science Genetic Algorithm Topic - Genetic Algorithm related Publications towards Data Science
- Towards Data Science Genetic Algorithm Topic - Genetic Algorithm related Publications towards Data Science
- Towards Data Science Genetic Algorithm Topic - Genetic Algorithm related Publications towards Data Science
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Bloggers
- datascopeanalytics
- Wes McKinney - Wes McKinney Archives.
- Matthew Russell - Mining The Social Web.
- Greg Reda - Greg Reda Personal Blog
- Julia Evans - Recurse Center alumna
- Hakan Kardas - Personal Web Page
- Sean J. Taylor - Personal Web Page
- Drew Conway - Personal Web Page
- Hilary Mason - Personal Web Page
- Noah Iliinsky - Personal Blog
- Matt Harrison - Personal Blog
- Vamshi Ambati - AllThings Data Sciene
- Prash Chan - Tech Blog on Master Data Management And Every Buzz Surrounding It
- Clare Corthell - The Open Source Data Science Masters
- Paul Miller
- Data Science London - profit organization dedicated to the free, open, dissemination of data science.
- Datawrangling
- Quora Data Science - Data Science Questions and Answers from experts
- Siah
- Machine Learning Mastery
- Daniel Forsyth - Personal Blog
- Data Science Weekly - Weekly News Blog
- Revolution Analytics - Data Science Blog
- R Bloggers - R Bloggers
- The Practical Quant
- Yet Another Data Blog
- Spenczar - building to reporting.
- KD Nuggets
- Meta Brown - Personal Blog
- Data Scientist
- WhatSTheBigData
- Tevfik Kosar - Magnus Notitia
- New Data Scientist
- Harvard Data Science - Thoughts on Statistical Computing and Visualization
- Data Science 101 - Learning To Be A Data Scientist
- Kaggle Past Solutions
- Adventures in Data Land
- Learning Lover
- Dataists
- Data-Mania
- Data-Magnum
- P-value - Musings on data science, machine learning, and stats.
- Digital transformation
- Data Mania Blog - [The File Drawer](https://chris-said.io/) - Chris Said's science blog
- Emilio Ferrara's web page
- DataNews
- Reddit TextMining
- Periscopic
- Hilary Parker
- Data Science Lab
- Meaning of
- DATA MINERS BLOG
- Dataclysm
- FlowingData - Visualization and Statistics
- Calculated Risk
- O'reilly Learning Blog
- Dominodatalab
- i am trask - A Machine Learning Craftsmanship Blog
- Vademecum of Practical Data Science - Handbook and recipes for data-driven solutions of real-world problems
- Dataconomy - A blog on the newly emerging data economy
- Springboard - A blog with resources for data science learners
- Analytics Vidhya - A full-fledged website about data science and analytics study material.
- Occam's Razor - Focused on Web Analytics.
- Data School - Data science tutorials for beginners!
- Colah's Blog - Blog for understanding Neural Networks!
- Sebastian's Blog - Blog for NLP and transfer learning!
- Distill - Dedicated to clear explanations of machine learning!
- Chris Albon's Website - Data Science and AI notes
- Andrew Carr - Data Science with Esoteric programming languages
- floydhub - Blog for Evolutionary Algorithms
- Jingles - Review and extract key concepts from academic papers
- nbshare - Data Science notebooks
- Deep and Shallow - All things Deep and Shallow in Data Science
- Loic Tetrel - Data science blog
- Chip Huyen's Blog - ML Engineering, MLOps, and the use of ML in startups
- Maria Khalusova - Data science blog
- Aditi Rastogi - ML,DL,Data Science blog
- Santiago Basulto - Data Science with Python
- Akhil Soni - ML, DL and Data Science
- Akhil Soni - ML, DL and Data Science
- Dataclysm
- Dataclysm
- Dataclysm
- Dataclysm
- Dataclysm
- Dataclysm
- Dataclysm
- Dataclysm
- Dataclysm
- Sebastian's Blog - Blog for NLP and transfer learning!
- Dataclysm
- Dataclysm
- Dataclysm
- Dataclysm
- Dataclysm
- Dataclysm
- Dataclysm
- Dataclysm
- Dataclysm
- Dataclysm
- Dataclysm
- Dataclysm
- Dataclysm
- Dataclysm
- Dataclysm
- Dataclysm
- Dataclysm
- Dataclysm
- Dataclysm
- Adventures in Data Land
- datascientistjourney
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Books
- Deep Learning Cookbook
- Data Science From Scratch: First Principles with Python
- Artificial Intelligence with Python - Tutorialspoint
- Machine Learning from Scratch
- Probabilistic Machine Learning: An Introduction
- A Comprehensive Guide to Machine Learning
- How to Lead in Data Science - Early Access
- Fighting Churn With Data
- Data Science at Scale with Python and Dask
- The Data Science Handbook: Advice and Insights from 25 Amazing Data Scientists
- Think Like a Data Scientist
- Introducing Data Science
- Practical Data Science with R
- Everyday Data Science
- Exploring Data Science - free eBook sampler
- Exploring the Data Jungle - free eBook sampler
- Classic Computer Science Problems in Python
- Math for Programmers
- R in Action, Third Edition
- Data Science Bookcamp
- Data Science Thinking: The Next Scientific, Technological and Economic Revolution
- Applied Data Science: Lessons Learned for the Data-Driven Business
- The Data Science Handbook
- Essential Natural Language Processing - Early access
- Mining Massive Datasets - free e-book comprehended by an online course
- Pandas in Action - Early access
- Genetic Algorithms and Genetic Programming
- Advances in Evolutionary Algorithms - Free Download
- Genetic Programming: New Approaches and Successful Applications - Free Download
- Evolutionary Algorithms - Free Download
- Advances in Genetic Programming, Vol. 3 - Free Download
- Global Optimization Algorithms: Theory and Application - Free Download
- Genetic Algorithms and Evolutionary Computation - Free Download
- Convex Optimization - Convex Optimization book by Stephen Boyd - Free Download
- R for Data Science
- Build a Career in Data Science
- Machine Learning Bookcamp - Early access
- Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, 2nd Edition
- Effective Data Science Infrastructure
- Practical MLOps: How to Get Ready for Production Models
- Regression, a Friendly guide - Early Access
- Streaming Systems: The What, Where, When, and How of Large-Scale Data Processing
- Data Science at the Command Line: Facing the Future with Time-Tested Tools
- Machine Learning - CIn UFPE
- Machine Learning with Python - Tutorialspoint
- Deep Learning
- Designing Cloud Data Platforms - Early Access
- The Elements of Statistical Learning: Data Mining, Inference, and Prediction
- Deep Learning with PyTorch
- Neural Networks and Deep Learning
- Introduction to Machine Learning with Python
- Artificial Intelligence: Foundations of Computational Agents, 2nd Edition - Free HTML version
- The Quest for Artificial Intelligence: A History of Ideas and Achievements - Free Download
- Graph Algorithms for Data Science - Early Access
- Data Mesh in Action - Early Access
- Regular Expression Puzzles and AI Coding Assistants
- Dive into Deep Learning
- Data for All
- Foundations of Data Science
- Comet for DataScience: Enhance your ability to manage and optimize the life cycle of your data science project
- Software Engineering for Data Scientists - Early Access
- Julia for Data Science - Early Access
- Machine Learning For Absolute Beginners
- eBook sale - Save up to 45% on eBooks!
- Causal Machine Learning
- Managing ML Projects
- Causal Inference for Data Science
- Data for All
- Data Analysis with Python and PySpark
- Casual Inference for Data Science - Early Access
- An Introduction to Statistical Learning - Download Page
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Newsletters
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Presentations
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Podcasts
- AI at Home
- AI Today
- Adversarial Learning
- Becoming a Data Scientist
- Chai time Data Science
- Data Crunch
- Data Engineering Podcast
- Data Science at Home
- Data Science Mixer
- Data Skeptic
- Datacast
- DataFramed
- DataTalks.Club
- Gradient Dissent
- Learning Machines 101
- Let's Data (Brazil)
- Linear Digressions
- Not So Standard Deviations
- O'Reilly Data Show Podcast
- Partially Derivative
- Superdatascience
- The Data Engineering Show
- The Radical AI Podcast
- The Robot Brains Podcast
- What's The Point
- How AI Built This
- DataFramed
- Data Stories
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YouTube Videos & Channels
- What is machine learning?
- Andrew Ng: Deep Learning, Self-Taught Learning and Unsupervised Feature Learning
- Data36 - Data Science for Beginners by Tomi Mester
- Deep Learning: Intelligence from Big Data
- Interview with Google's AI and Deep Learning 'Godfather' Geoffrey Hinton
- Introduction to Deep Learning with Python
- What is machine learning, and how does it work?
- Data School - Data Science Education
- Neural Nets for Newbies by Melanie Warrick (May 2015)
- Neural Networks video series by Hugo Larochelle
- Google DeepMind co-founder Shane Legg - Machine Super Intelligence
- Data Science Primer
- Data Science with Genetic Algorithms
- Data Science for Beginners
- DataTalks.Club
- mlops.community - Interviews of industry experts about production ML
- ML Street Talk - Unabashedly technical and non-commercial, so you will hear no annoying pitches.
- Neural networks from scratch by Sentdex
- Manning Publications YouTube channel
- Ask Dr Chong: How to Lead in Data Science - Part 1
- Ask Dr Chong: How to Lead in Data Science - Part 2
- Ask Dr Chong: How to Lead in Data Science - Part 3
- Ask Dr Chong: How to Lead in Data Science - Part 4
- Ask Dr Chong: How to Lead in Data Science - Part 5
- Ask Dr Chong: How to Lead in Data Science - Part 6
- Regression Models: Applying simple Poisson regression
- Deep Learning Architectures
- Time Series Modelling and Analysis
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Real World
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Disaster
- deprem-ml - sourced [afet.org](https://afet.org).
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What is Data Science?
- What is Data Science @ O'reilly
- The sexiest job of 21st century
- Wikipedia
- How to Become a Data Scientist
- Software Development Resources for Data Scientists - ready code and tools._|
- Navigating Your Path to Becoming a Data Scientist - demand careers today. With businesses increasingly relying on data to make decisions, the need for skilled data scientists has grown rapidly. Whether it’s tech companies, healthcare organizations, or even government institutions, data scientists play a crucial role in turning raw data into valuable insights. But how do you become a data scientist, especially if you’re just starting out? _|
- a very short history of #datascience - -computer science. The term “Data Science” has emerged only recently to specifically designate a new profession that is expected to make sense of the vast stores of big data. But making sense of data has a long history and has been discussed by scientists, statisticians, librarians, computer scientists and others for years. The following timeline traces the evolution of the term “Data Science” and its use, attempts to define it, and related terms._ |
- Data Scientist Roadmap - driven world where approx 328.77 million terabytes of data are generated daily. And this number is only increasing day by day, which in turn increases the demand for skilled data scientists who can utilize this data to drive business growth._|
- What is Data Science @ Quora
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Where do I Start?
- Python - generated packages. To install packages, there are two main methods: Pip (invoked as `pip install`), the package manager that comes bundled with Python, and [Anaconda](https://www.anaconda.com) (invoked as `conda install`), a powerful package manager that can install packages for Python, R, and can download executables like Git.
- Scikit-Learn - purpose data science package which implements the most popular algorithms - it also includes rich documentation, tutorials, and examples of the models it implements. Even if you prefer to write your own implementations, Scikit-Learn is a valuable reference to the nuts-and-bolts behind many of the common algorithms you'll find. With [Pandas](https://pandas.pydata.org/), one can collect and analyze their data into a convenient table format. [Numpy](https://numpy.org/) provides very fast tooling for mathematical operations, with a focus on vectors and matrices. [Seaborn](https://seaborn.pydata.org/), itself based on the [Matplotlib](https://matplotlib.org/) package, is a quick way to generate beautiful visualizations of your data, with many good defaults available out of the box, as well as a gallery showing how to produce many common visualizations of your data.
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- Kenneth Cukier - author of Big Data (http://www.big-data-book.com/). |
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- INEVITABLE - up Company based in England, UK |
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Fun
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Datasets
- grouplens.org
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- ClimateData.us
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- UC Irvine Machine Learning Repository - contains data sets good for machine learning
- research-quality data sets
- Academic Torrents
- ADS-B Exchange - Specific datasets for aircraft and Automatic Dependent Surveillance-Broadcast (ADS-B) sources.
- A Deep Catalog of Human Genetic Variation
- data.gov - The home of the U.S. Government's open data
- United States Census Bureau
- usgovxml.com
- enigma.com - Navigate the world of public data - Quickly search and analyze billions of public records published by governments, companies and organizations.
- datahub.io
- aws.amazon.com/datasets
- datacite.org
- The official portal for European data
- NASDAQ:DATA - Nasdaq Data Link A premier source for financial, economic and alternative datasets.
- figshare.com
- GeoLite Legacy Downloadable Databases
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- MapLight - provides a variety of data free of charge for uses that are freely available to the general public. Click on a data set below to learn more
- GHDx - Institute for Health Metrics and Evaluation - a catalog of health and demographic datasets from around the world and including IHME results
- St. Louis Federal Reserve Economic Data - FRED
- New Zealand Institute of Economic Research – Data1850
- UNICEF Data
- undata
- NASA SocioEconomic Data and Applications Center - SEDAC
- The GDELT Project
- StackExchange Data Explorer - an open source tool for running arbitrary queries against public data from the Stack Exchange network.
- SocialGrep - a collection of open Reddit datasets.
- San Fransisco Government Open Data
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- Open data Index
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Infographics
- <img src="https://i.imgur.com/0OoLaa5.png" width="150" /> - differences-of-a-data-scientist-vs-data-engineer) |
- <img src="https://cloud.githubusercontent.com/assets/182906/19517857/604f88d8-960c-11e6-97d6-16c9738cb824.png" width="150" />
- <img src="https://i.imgur.com/W2t2Roz.png" width="150" />
- <img src="https://i.imgur.com/rb9ruaa.png" width="150" /> - a-data-scientist/). |
- <img src="https://i.imgur.com/XBgKF2l.png" width="150" />
- <img src="https://i.imgur.com/l9ZGtal.jpg" width="150" />
- <img src="https://i.imgur.com/TWkB4X6.png" width="150" />
- <img src="https://i.imgur.com/gtTlW5I.png" width="150" />
- <img src="https://scikit-learn.org/stable/_static/ml_map.png" width="150" />
- <img src="https://i.imgur.com/3JSyUq1.png" width="150" />
- <img src="https://i.imgur.com/DQqFwwy.png" width="150" />
- <img src="https://www.springboard.com/blog/wp-content/uploads/2016/03/20160324_springboard_vennDiagram.png" width="150" height="150" /> - science-career-paths-different-roles-industry/) by Springboard |
- <img src="https://data-literacy.geckoboard.com/assets/img/data-fallacies-to-avoid-preview.jpg" width="150" alt="Data Fallacies To Avoid" /> - data scientist/non-statistician colleagues [how to avoid mistakes with data](https://data-literacy.geckoboard.com/poster/). From Geckoboard's [Data Literacy Lessons](https://data-literacy.geckoboard.com/). |
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