Foundational Python for Data Science
暫譯: 數據科學基礎 Python

Behrman, Kennedy

商品描述

Data science and machine learning - two of the world's hottest fields - are attracting talent from a wide variety of technical, business, and liberal arts disciplines. Python, the world's #1 programming language, is also the most popular language for data science and machine learning. This is the first guide specifically designed to help millions of people with widely diverse backgrounds learn Python so they can use it for data science and machine learning.

Leading data science instructor and practitioner Kennedy Behrman first walks through the process of learning to code for the first time with Python and Jupyter notebook, then introduces key libraries every Python data science programmer needs to master. Once you've learned these foundations, Behrman introduces intermediate and applied Python techniques for real-world problem-solving.

Throughout, Foundational Python for Data Science presents hands-on exercises, learning assessments, case studies, and more - all created with colab (jupyter compatible) notebooks, so you can execute all coding examples interactively without installing or configuring any software.

商品描述(中文翻譯)

資料科學和機器學習是當今世界上最熱門的兩個領域,吸引了來自各種技術、商業和人文學科的人才。Python,全球第一的程式語言,也是資料科學和機器學習中最受歡迎的語言。本書是專門為數百萬來自不同背景的人設計的指南,幫助他們學習Python,以便能夠應用於資料科學和機器學習。

資深資料科學講師及實務專家Kennedy Behrman首先帶領讀者了解如何首次使用Python和Jupyter notebook進行編程,然後介紹每位Python資料科學程式設計師必須掌握的關鍵函式庫。一旦掌握了這些基礎知識,Behrman將介紹中級和應用的Python技術,以解決實際問題。

在整本書中,資料科學的基礎Python提供了實作練習、學習評估、案例研究等內容,所有內容均使用colab(與Jupyter相容)筆記本創建,因此您可以互動式地執行所有程式碼範例,而無需安裝或配置任何軟體。

作者簡介

Kennedy Behrman is a veteran software and data engineer. He first used Python writing asset management systems in the Visual Effects industry. He then moved into the startup world, using Python at startups using machine learning to characterize videos and predict the social media power of athletes.

作者簡介(中文翻譯)

Kennedy Behrman 是一位資深的軟體和數據工程師。他最初在視覺特效產業中使用 Python 編寫資產管理系統。之後,他進入創業界,利用 Python 在初創公司中使用機器學習來特徵化視頻並預測運動員的社交媒體影響力。

最後瀏覽商品 (20)