Mastering Deep Learning with Python: 2 Manuscripts: The Ultimate Step By Step Guide To Learn Mastering Deep Learning & Python In 7 Days Front Cover

Mastering Deep Learning with Python: 2 Manuscripts: The Ultimate Step By Step Guide To Learn Mastering Deep Learning & Python In 7 Days

  • Length: 335 pages
  • Edition: 1
  • Publication Date: 2020-12-26
  • ISBN-10: B08RCSJ39K
  • Sales Rank: #55035 (See Top 100 Books)
Description

Mastering Deep Learning with Python: 2 Manuscripts

This book presents the knowledge and technologies that will allow us to participate in this new era of information, governed by Big Data and machine learning, the life of the data is analyzed step by step, showing how to obtain it, store it, process it, visualize it, and draw conclusions from it: that is, show the data analysis as it is: a fascinating area, It requires many hours of careful work. Likewise, the Python programming language is analyzed, the most used in data Science due to the multitude of libraries that it facilitates, but is not limited to the standard, but presents current technologies that, with Python as an interface, will allow scaling the size of the data to the maximum. Therefore, our journey with the data will take us, for example, to know the MongoDB database and the Spark processing environment.

In this book, you will discover:

  • What is a data scientist?
  • What languages should be learned?
  • The three musketeers of Data Science
  • Python introduction
  • Languages do you need to learn for data science

These are some of the topics covered in this book:

  • Machine Learning Algorithms
  • K NN – Nearest Neighbor Method
  • SVC – Support vector machine
  • Mathematics for Data Analysis
  • Working with Threads in Python
  • Working with processes in Python

These are some of the topics covered in this book:

  • fundamentals of deep learning
  • fundamentals of probability
  • fundamentals of statistics
  • fundamentals of linear algebra
  • introduction to machine learning and deep learning
  • fundamentals of machine learning
  • fundamentals of neural networks and deep learning
  • deep learning parameters and hyper-parameters
  • deep neural networks layers
  • deep learning activation functions
  • convolutional neural network
  • Deep learning in practice (in jupyter notebooks)
  • python data structures
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