[PDF] Essential Math for Data Science: Take

Essential Math for Data Science: Take Control of Your Data with Fundamental Calculus, Linear Algebra, Probability, and Statistics. Hadrien Jean

Essential-Math-for-Data-Science.pdf
ISBN: 9781098115562 | 250 pages | 7 Mb

• Essential Math for Data Science: Take Control of Your Data with Fundamental Calculus, Linear Algebra, Probability, and Statistics
• Hadrien Jean
• Page: 250
• Format: pdf, ePub, fb2, mobi
• ISBN: 9781098115562
• Publisher: O'Reilly Media, Incorporated

Download Essential Math for Data Science: Take Control of Your Data with Fundamental Calculus, Linear Algebra, Probability, and Statistics

Downloading pdf books for free Essential Math for Data Science: Take Control of Your Data with Fundamental Calculus, Linear Algebra, Probability, and Statistics in English MOBI 9781098115562 by Hadrien Jean

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

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Essential Math for Data Science - Posts
I just released my book "Essential Math for Data Science"🎉. The idea is to use a hands-on approach using examples in Python python icon 1.1.1 From Computer Programming to Calculus; 1.1.2 Unknowns; 1.1.3 In Chapter 08, we'll use many linear algebra concepts from previous chapters to learn 

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