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

Mathematics for Machine Learning

Credits - Garrett Thomas

#data #datascience #machinelearning #deeplearning #dataanalytics #dataanalysis

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Python for Data Science ***Quick Reference Sheet***

#python #dataanalysis #datascience #machinelearning #deeplearning

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Numpy ***100 Exercises***

#pythonprogramming #python #dataanalysis #datascience

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****Python for Data Analysis by Boston University****

#datascience #dataanalysis #dataanalytics #python #analytics

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Data Visualization is a very important step in Data Science, so we should try to MASTER it.

Here are the useful links for Data Visualization -

1)Quick and Easy Data Visualizations in Python with Code.
(https://lnkd.in/fXJ-_Y8)

2)10 Useful Python Data Visualization Libraries for Any Discipline.
(https://lnkd.in/fBxbHwr)

3)Top 50 matplotlib Visualizations – The Master Plots (with full python code).
(https://lnkd.in/fGrnGax)

4)Data Visualization Effectiveness Profile.
(https://lnkd.in/f3v52Fd)

5)The Visual Perception of Variation in Data Displays.
(https://lnkd.in/fm-TbPM)

6)Matplotlib Tutorial – A Complete Guide to Python Plot w/ Examples.
(https://lnkd.in/fFkUgQP)

7)Interactive Data Visualization in Python With Bokeh.
(https://lnkd.in/fEfQAvg)

8) Data Visualization in R
https://lnkd.in/fEvZB_N

9) The Next Level of Data Visualization in Python (Plotly)
https://lnkd.in/fKn4cPM

#datascience #dataanalysis #datavisualization #python #r

✴️ @AI_Python_EN

Empowering you to use machine learning to get valuable insights from data.

🔥 Implement basic ML algorithms and deep neural networks with PyTorch.
🖥 Run everything on the browser without any set up using Google Colab.
📦 Learn object-oriented ML to code for products, not just tutorials.

Github Link - https://lnkd.in/f8nu8UR

#datascience #data #dataanalysis #ml #machinelearning #deeplearning #ai #artificialintelligence

✴️ @AI_Python_EN

📚📖 Python Machine Learning Tutorial 📖📚

➡️ Python Machine Learning – Tasks and Applications ( https://lnkd.in/fZcs-xE)
➡️ Python Machine Learning Environment Setup – Installation Process (https://lnkd.in/fJHwbjr)
➡️ Data Preprocessing, Analysis & Visualization (https://lnkd.in/fVz58kJ)
➡️ Train and Test Set (https://lnkd.in/fq_GXjn)
➡️ Machine Learning Techniques with Python (https://lnkd.in/fjdsQzd)
➡️ Top Applications of Machine Learning (https://lnkd.in/f-CNyK2)
➡️ Machine Learning Algorithms in Python – You Must Learn (https://lnkd.in/fTxCA23)

#python #machinelearning #datascience #data #dataanalysis #artificialintelligence #ai #visualization #algorithms

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#imbalancedData
What is it?
Ans-> Suppose, you are having a Classification problem with 2M records. The Output variable is having 2 categories (Yes- 500, No- 1.99M or more).

This is the imbalanced data, as one category is far less than the other category in the Output variable.

Examples-> Credit Card fraud, Cancer Detection(or any other disease that is severe), and many more.

How to deal with it?
1) Undersampling
2) Oversampling

#datascience #dataanalysis #learning

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Great Statistical software for Beginners.

Here is the Gretl Tutorial by Simone Gasperin

1)Simple Linear Regression
https://lnkd.in/ecfsV9c

2)Coding Dummy Variables
https://lnkd.in/ef7Yd7f

3)Forecasting New Observations
https://lnkd.in/eNKbxbU

4)Forecasting a Large Number of Observations
https://lnkd.in/eHmibGs

5)Logistic Regression
https://lnkd.in/eRfhQ87

6)Forecasting and Confusion Matrix
https://lnkd.in/eaqrFJr

7)Modeling and Forecasting Time Series Data
https://lnkd.in/e6fqKpF

8)Comparing Time Series Trend Models
https://lnkd.in/eKjEUAE

#datascience #machinelearning #statistics #dataanalytics #dataanalysis

✴️ @AI_Python_EN