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

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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, mobi, fb2
ISBN: 9781098115562
Publisher: O'Reilly Media, Incorporated

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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 : Take Control of Your Data with with Fundamental Calculus, Linear Algebra, Probability, and Statistics 
Essential Math for Data Science: Take Control of Your Data
Essential Math for Data Science: Take Control of Your Data with Fundamental Calculus, Linear Algebra, Probability, and Statistics: Jean, Hadrien: Amazon.ae.
Essential Math For Data Science: How To Make Use Of Data
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Mathematical Sciences | 17881 | Course Descriptions
I The topics for integral calculus (MA 1022) are covered in this course: the concept of the The course is intended not only for beginning mathematics, statistics or techniques, and to applications of linear algebra, particularly to Data Science. Topics to be covered are: basic probability theory including Bayes theorem; 
Essential Math for Data Science - Data Science Central
Data summaries and descriptive statistics, central tendency, variance, covariance, correlation, · Basic probability: basic idea, expectation, 
Create your own Online Data Science Education Curriculum
Get top-rated Data Science education at a cost of $1.09 a day with Statistics with Python Specialization by University of Michigan Discrete Mathematics, Calculus, Linear Algebra and Probability are covered. Learners are introduced to the fundamental programming concepts including data structures,