📚📝 Knowledge Library 💼📦

Data Science | Business Intelligence | Artificial Intelligence | Python | Statistics | SQL

Books | Cheat Sheets | Notes | Platforms | YouTube | Articles | Documentations | Websites

Important Libraries

1. Pandas : Data Analysis | Data Manipulation | Data Import and Export

2. NumPy : Numerical Python | N Dimensional Array | Linear Algebra and Mathematical Functions | Elementwise Matrix Operations

3. SciPy : Scientific Calculations | Linear Algebra | Integration | Signal and Image Processing

4. Matplotlib : Data Interactive Visualization | Charts, Plots and Graphs

5. Seaborn : Data Interactive Visualization | Statistical Graphs

6. Plotly : Javascript Interactive Web based Visualization | Charts, Plots and Graphs

7. Bokeh : Interactive Visualization Library for Modern Web Browsers | High Performance Interactivity

8. Scikit Learn : Predictive Data Analysis | Machine Learning Models

9. TensorFlow : Machine Learning Platform | Google Brain Team | Neural Network

10. Keras : API | Deep Learning Framework

11. OpenCV : Real Time Computer Vision | Machine Learning | Image Processing | Identify Object

12. PyTorch : Computer Vision | Natural Language Processing | Facebook's Research Group

Markdown

• Markdown Guide | Markdown Presentation | Table Generator

Data Science Specialist

• Chris Albon
• Real Python
• The Clever Programmer
• Data School

Statistics

• Math is Fun

Artificial Intelligence

• Elements of AI | Building AI

YouTube

• Data Professor
• Corey Scafer
• Edureka
• Simplilearn
• Data School
• Code Basics
• Free Code Camp
• Simple Learning Pro
• CampusX

Website

• SQL Online
• SQLBI
• Data Quest
• Educative
• Edpresso
• Dataconomy
• Python Examples
• Programiz
• Matplotlib Plots
• Scribbr
• Quantdare
• Machine Learning for Everyone
• Ultimate Cheat Sheet

Udemy

• Maven Analytics ( Analytics and Business Intelligence )
• Chris Dutton ( Owner of Maven Analytics )
• Aaron Parry ( Power BI )
• Lan Little John ( Excel, Power BI and Data Studio )
• Dustin Cabral ( Tableau Expert )
• Leila Gharani ( Microsoft Most Valuable Professional )
• Kirill Eremenko ( Data Science, Machine Learning and Deep Learning )
• Jose Portilla ( Data Science )
• Andrei Neagoie ( Data Science, Web Design and Development, Python )
• Daniel Bourke ( Machine Learning )
• Dr. Angela Yu ( Web Design and Development, Python )
• Mariel Aim ( Business Intelligence )
• Data is Good Academy ( Data Science, BI and AI )
• Dee Naidoo ( Tableau )
• Nikolai Schuler ( Power BI )
• New Horizon ( Data Analysis )
• Microsoft Excel Data Analysis ( Excel )

Linked Learning

• Google Cloud
• John Rischin
• Chris Dalla Villa
• Michael Taylor
• Bill Shander ( Data Visualization )
• Curt Frye
• Robin Hunt ( Data Analytics )
• Nick Brazzi ( Productivity )
• Jess Stratton ( Productivity )
• Garrick Chow ( Productivity and Mobile )
• Adam Wilbert ( Database and SQL )
• David Rivers ( Microsoft and Google Productivity )
• Lillian Pierson ( Python for Data Science )
• Sahil Malik ( Azure Machine Learning )
• Ben Sullins ( Python )
• Keith McCormick ( Predictive Analytics )
• Dennis Taylor ( Spreadsheet )
• Robin Andrews ( Python Data Structure & Algorithms )

Google

• Deep Mind
• Google AI
• Generative AI
• PaLM 2
• Research
• Responsible AI
• Search Lab
• Data Science on Google Cloud
• Google Workspace
• Grow with Google

Medium

• Arpita Ghosh ( Power BI )

Design

• Paint 3d