Data Science From Scratch (Part 1-2)

Автор: TRex от 5-07-2021, 08:32, Коментариев: 0

Категория: КНИГИ » ПРОГРАММИРОВАНИЕ

Название: Data Science From Scratch (Part 1-2)
Автор: Dr. Junaid S Qazi
Издательство: Leanpub
Год: 2021
Формат: PDF
Страниц: 410+352
Размер: 116 Mb
Язык: English

I am pleased to mention that this book is based on lecture notes from my bestselling Bootcamp on Data Science and Machine Learning using Python. It was never easy to get enough time, and I am obliged to those, who kept on sending requests to compile my notes in the form of a book.

Thank you for making it happen :).
My fellows, I decided to split my notes into two books:

1: Data Science from Scratch (Part 1)

(1 to 400 pages)

Covers all what you need for advance business intelligence. Everything from scratch to the point where you can learn to implement data preprocess pipeline and presented insights. Most of the time, you only need this part for advance analytics. The idea here is to give you the skills so that you can quickly start looking for projects on freelancing platforms, there is a lot that you can do just after finishing the part 1.

2: Data Science from Scratch (Part 2)

(401 to ~ 900 pages)

This part will entirely focus on business machine learning, which will be available soon. It will cover theory and complete pipeline along with hands-on exercise for widely used machine learning algorithms. I will keep you posted!

This is an unedited copy and there might be some typo errors. However, all the codes are working and using latest versions of stable libraries till my last check. Keeping it with me and waiting for the final edits could take another year, which does not make much sense. So, I decided to bring the book to you with half of its original price. Whenever, the final copy will be available, you will get with no extra price, so a chance to get final copy with half price.

I am pleased to mention here, to my knowledge, this is the first ever book completely written in jupyter notebook so that, you feel real time working environment that is preferred by data science community.




ОТСУТСТВУЕТ ССЫЛКА/ НЕ РАБОЧАЯ ССЫЛКА ЕСТЬ РЕШЕНИЕ, ПИШИМ СЮДА!


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