Master the math needed to excel in data science and machine learning. If you’re a data scientist who lacks a math or scientific background or a developer who wants to add data domains to your skillset, this is your book. Author Hadrien Jean provides you with a foundation in math for data science, machine learning, and deep learning.
Through the course of this book, you’ll learn how to use mathematical notation to understand new developments in the field, communicate with your peers, and solve problems in mathematical form. You’ll also understand what’s under the hood of the algorithms you’re using.
Learn how to:
Use Python and Jupyter notebooks to plot data, represent equations, and visualize space transformations
Read and write math notation to communicate ideas in data science and machine learning
Perform descriptive statistics and preliminary observation on a dataset
Manipulate vectors, matrices, and tensors to use machine learning and deep learning libraries such as TensorFlow or Keras
Explore reasons behind a broken model and be prepared to tune and fix it
Choose the right tool or algorithm for the right data problem
具体描述
读后感
评分
评分
评分
评分
用户评价
相关图书
本站所有内容均为互联网搜索引擎提供的公开搜索信息，本站不存储任何数据与内容，任何内容与数据均与本站无关，如有需要请联系相关搜索引擎包括但不限于百度，google,bing,sogou 等
© 2025 book.wenda123.org All Rights Reserved. 图书目录大全 版权所有