5. Data Science at the Command Line

Publisher: O'Reilly

jeroenjanssens.com/dsatcl/

10 Data Science Books

6. Introduction to Probability for Data Science

Publisher: Michigan University

probability4datascience.com

7. Think Stats

Publisher: O'Reilly

https://greenteapress.com/thinkstats2/thinkstats2.pdf

8. Mining Social Media

Publisher: No Starch Press

🖇️ socialdata.site

9. Kafka, The Definitive Guide

Publisher: O'Reilly

https://assets.confluent.io/m/2849a76e39cda2bd/original/20201119-EB-Kafka_The_Definitive_Guide-Preview-Chapters_1_thru_6.pdf

10 Data Science Books

10. Python Data Science Handbook

Publisher: O'Reilly

HTML: https://jakevdp.github.io/PythonDataScienceHandbook/

PDF: https://github.com/terencetachiona/Python-Data-Science-Handbook/blob/master/Python%20Data%20Science%20Handbook%20-%20Jake%20VanderPlas.pdf

10 Data Science Books

One day or Day one. You decide.

Data Science edition.

𝗢𝗻𝗲 𝗗𝗮𝘆 : I will learn SQL.
𝗗𝗮𝘆 𝗢𝗻𝗲: Download mySQL Workbench.

𝗢𝗻𝗲 𝗗𝗮𝘆: I will build my projects for my portfolio.
𝗗𝗮𝘆 𝗢𝗻𝗲: Look on Kaggle for a dataset to work on.

𝗢𝗻𝗲 𝗗𝗮𝘆: I will master statistics.
𝗗𝗮𝘆 𝗢𝗻𝗲: Start the free Khan Academy Statistics and Probability course.

𝗢𝗻𝗲 𝗗𝗮𝘆: I will learn to tell stories with data.
𝗗𝗮𝘆 𝗢𝗻𝗲: Install Power BI and create my first chart.

𝗢𝗻𝗲 𝗗𝗮𝘆: I will become a Data Data Analyst.
𝗗𝗮𝘆 𝗢𝗻𝗲: Update my resume and apply to some Data Science job postings.

Don't aim for this:

Excel - 100%
SQL - 0%
PowerBI/Tableau - 0%
Python/R - 0%

Aim for this:

Excel - 25%
SQL - 25%
PowerBI/Tableau - 25%
Python/R - 25%

You don't need to know everything straight away.

"Here are the some Natural Language Processing Projects"

Advanced Python Scheduler (APScheduler) is a Python library for scheduling code to run later, once or periodically.
You can add new "jobs" or delete old ones on the fly at your discretion.

If you save your jobs to the database, they will also outlast a program restart and keep their state.

💬 A Text Attention Network for Spatial Deformation Robust Scene Text Image Super-resolution

Github: https://github.com/mjq11302010044/tatt

Paper: https://arxiv.org/abs/2203.09388v2

Dataset: https://deepchecks.com/blog/