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10 Weeks, 20 Lessons, Data Science for All!
طی ۱۰ هفته و ۲۰ درس به همراه تمرینهای این کتاب دانش ابتدایی در مورد data science کسب کنید.
#book #free #github #microsoft #data #science #data_science #beginner
@pythony
microsoft.github.io/Data-Science-For-Beginners
🆔 @code_pedia
طی ۱۰ هفته و ۲۰ درس به همراه تمرینهای این کتاب دانش ابتدایی در مورد data science کسب کنید.
#book #free #github #microsoft #data #science #data_science #beginner
@pythony
microsoft.github.io/Data-Science-For-Beginners
🆔 @code_pedia
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یکی از بهترین منبع ها برای data structures و algorithm این ریپو هست به همراه کد و animation به زبانهای مختلف. برای مصاحبه های تکنیکال هم عالیه. دنبال ترجمه به زبانهای دیگه هم هستن. یک ورژن برای فارسی خیلی خوب میشه.
Github: https://github.com/krahets/hello-algo/blob/main/en/README.md
#data_science
🆔 @code_pedia
Github: https://github.com/krahets/hello-algo/blob/main/en/README.md
#data_science
🆔 @code_pedia
👍5
Data Science_A First Intro_Python.pdf
23.3 MB
Data Science: A First Introduction with Python
#Data_Science: A First Introduction with Python explores using the Python programming language in Jupyter notebooks to manipulate and cleanse data, create powerful visualizations, and extract insights from data using classification, regression, clustering, and inference. Emphasis is placed on clear, repeatable and accessible workflows, as well as the fundamentals of version control. Based on educational research and active learning principles, the book takes a modern approach to #Python and includes accompanying autograded Jupyter worksheets for interactive, self-paced learning. The text will allow readers to be well prepared for working on projects in the field of Data Science. It is intended for students of all majors with minimal prior knowledge of mathematics and programming.
❤️مخصوص دیتا ساینس کارها😎😎
🆔 @code_pedia
#Data_Science: A First Introduction with Python explores using the Python programming language in Jupyter notebooks to manipulate and cleanse data, create powerful visualizations, and extract insights from data using classification, regression, clustering, and inference. Emphasis is placed on clear, repeatable and accessible workflows, as well as the fundamentals of version control. Based on educational research and active learning principles, the book takes a modern approach to #Python and includes accompanying autograded Jupyter worksheets for interactive, self-paced learning. The text will allow readers to be well prepared for working on projects in the field of Data Science. It is intended for students of all majors with minimal prior knowledge of mathematics and programming.
❤️مخصوص دیتا ساینس کارها😎😎
🆔 @code_pedia
❤🔥7