Essential Math for Data Science - No Cost Library

Essential Math for Data Science: take control of your data with fundamental calculus, linear algebra, probability, and statistics

   Author(s): Hadrien Jean  

        Publisher: O'Reilly Media, Year: 2020

                                        

 Description: 

Master the math required for data science and machine learning to succeed. This is your book whether you are a computer scientist who lacks technical or theoretical experience or a developer who needs to incorporate data domains into your ability set. Author Hadrien Jean gives you a base for data analysis, artificial learning, and deep learning in mathematics. You will learn how to use mathematical notation to understand new advances in the field, interact with your colleagues, and solve problems in mathematical form over the course of this book. Even, you'll learn what the equations you are using are under the hood. 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 E E Learn how to: use Python and Jupyter notebooks to map data, represent equations and imagine space transformations.

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