A Brief History of Data Science (Pre-2010, i.e. prior to rise of deep learning & popular usage of the term "data science")
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Note: Modified original version of infographic to add 3 seminal developments in the history of Artificial Intelligence:

- 1943: Artificial neuron model (McCulloch & Pitts)
- 1950: Turing Test (Alan Turing)
- 1956: Dartmouth Conference (McCarthy, Minsky, Shannon)

#datascience #statistics #analytics #machinelearning #bigdata #artificialintelligence #innovation #technology #history #ai #datamining #informatics #infographics #informationtechnology #computerscience #dataanalysis #deeplearning #neuroscience #mathematics #science

🗣 @AI_Python_Arxiv
✴️ @AI_Python_EN
❇️ @AI_Python

All ***Cheat Sheets*** in one place.

Github link - https://lnkd.in/fGeGXQs

#datascience #machinelearning #excel #deeplearning #python #R #sql #matlab #datamining #datawarehousing

✴️ @AI_Python_EN

Machine Learning (ML) & Artificial Intelligence (AI): From Black Box to White Box Models in 4 Steps - Resources for Explainable AI & ML Model Interpretability.

✔️STEP 1 - ARTICLES

- (short) KDnuggets article: https://lnkd.in/eRyTXcQ

- (long) O'Reilly article: https://lnkd.in/ehMHYsr

✔️STEP 2 - BOOKS

- Interpretable Machine Learning: A Guide for Making Black Box Models Explainable (free e-book): https://lnkd.in/eUWfa5y

- An Introduction to Machine Learning Interpretability: An Applied Perspective on Fairness, Accountability, Transparency, and Explainable AI (free e-book): https://lnkd.in/dJm595N

✔️STEP 3 - COLLABORATE

- Join Explainable AI (XAI) Group: https://lnkd.in/dQjmhZQ

✔️STEP 4 - PRACTICE

- Hands-On Practice: Open-Source Tools & Tutorials for ML Interpretability (Python/R): https://lnkd.in/d5bXgV7

- Python Jupyter Notebooks: https://lnkd.in/dETegUH

#machinelearning #datascience #analytics #bigdata #statistics #artificialintelligence #ai #datamining #deeplearning #neuralnetworks #interpretability #science #research #technology #business #healthcare

✴️ @AI_Python_EN

****Web Scraping in Python****

#DataScience #DataMining #WebMining #WebScraping

✴️ @AI_Python_EN

This is Your Brain on Code 🧠💻🔢 computer programming is often associated with math, but researchers used functional MRI scans to show the role of the brain's language processing centers: https://lnkd.in/eN_-3RA

#datascience #machinelearning #ai #bigdata #analytics #statistics #artificialintelligence #datamining #computing #programmers #neuroscience

✴️ @AI_Python_EN

This is the reference implementation of Diff2Vec - "Fast Sequence Based Embedding With Diffusion Graphs" (CompleNet 2018). Diff2Vec is a node embedding algorithm which scales up to networks with millions of nodes. It can be used for node classification, node level regression, latent space community detection and link prediction. Enjoy!

https://lnkd.in/dXiy5-U

#technology #machinelearning #datamining #datascience #deeplearning #neuralnetworks #pytorch #tensorflow #diffusion #Algorithms

✴️ @AI_Python_EN

#AI/ #DataScience/ #MachineLearning/ #ML:
7 Steps for Data Preparation Using #Python

Link => https://bit.ly/PyDataPrep

#datamining #statistics #bigdata #artificialintelligence

✴️ @AI_Python_EN

A PyTorch implementation of "SimGNN: A Neural Network Approach to Fast Graph Similarity Computation" (WSDM 2019). This is a lightweight graph convolutional neural network for the fast calculation of approximate graph similarity at scale. Graph similarity search is among the most important graph-based applications, e.g. finding the chemical compounds that are most similar to a query compound.

https://lnkd.in/gA5tfuC

#datamining #machinelearning #deeplearning #datascience #bigdata

✴️ @AI_Python_EN