Deep Learning: 2 Manuscripts - Analyzing Data with Power Bi and Convolutional Neural Networks in Python

Anthony Williams




Deep Learning - A 2-book BUNDLE!!

Book 1: Analyzing Data with Power BI

If you are thinking of doing some data science work, first you have to get familiar with data libraries, various techniques of data modelling, in other words you have to dive into data analysis discipline with some fundamental understanding of this science. This book provides you that, fundamental of business and data analytics and insight into various data models and algorithms all written having a beginner in mind. Further chapters will introduce you to powerful business analytics tool provided by Microsoft Power BI. By the time you are done with the book you will master business analytics modelling with Power BI and share it to other users who are interested in same topic as you are. Data analytics also may be the right answer for you if you are involved in marketing management since it can help you with operating, strategic and financial performance. On the other hand Power BI will let you to ask all the right questions and help you to make wise business decisions. If this sounds good to you, let`s dive in together into the data analysis with Power BI.

In this book you will learn:

  • Basics of data analysis processes
  • Fundamental data analysis algorithms
  • Basic of data and text mining, data visualization and business intelligence
  • Techniques used for analysing quantitative data
  • Basic data analysis tasks
  • Conceptual, logical and physical data models
  • Power BI service and data modelling
  • Creating reports and visualizations in Power BI
  • Data transformation and data cleaning in Power BI
  • Real world applications of data analysis
  • And much, much more!!

Book 2: Convolutional Neural Networks in Python

Deep learning has been a great part of various scientific fields and since this is my third book regarding this topic, you already know the great significance of deep learning in comparison to traditional methods. At this point, you are also familiar with types of neural networks and their wide range of applications including image and speech recognition, natural language processing, video game development and other. On the other hand, this book is all about convolutional neural networks and how to use these neural networks in various tasks of automatic image and speech recognition in Python. You will also get a better insight into the architecture of convolutional layers as we are going deeper into this subject. Deep learning is pretty complex subject, but since you already have a fundamental knowledge of this topic, getting to know convolutional neural networks better is next logical step.

In this book you will learn:

  • Architecture of convolutional neural networks
  • Solving computer vision tasks using convolutional neural networks
  • Python and computer vision
  • Automatic image and speech recognition
  • Theano and TenroeFlow image recognition
  • How to use MNIST vision dataset
  • What are commonly used convolutional filters
  • And much, much more!!

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