Learning Python Data Analysis [Video]

Learning Python Data Analysis [Video]

Benjamin Hoff

Analyze and understand your data with the power and simplicity of Python
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Video Description

Python features numerous numerical and mathematical toolkits such as: Numpy, Scipy, Scikit learn and SciKit, all used for data analysis and machine learning. With the aid of all of these, Python has become the language of choice for data scientists for data analysis, visualization, and machine learning.

This video aims to teach Python developers how to perform data analysis with the language by taking advantage of the core data science libraries in the Python ecosystem. The learning objective for viewers is to understand how to locate, manipulate, and analyse data with Python, with the ability to analyse large and small sets of data using libraries such as Numpy, pandas, IPython and SciPy.

This is a two part series. The first series is focused on getting and manipulation sizeable amounts of data using modern techniques. The second series is focused on advanced analysis of the data to include modern machine learning techniques.

Style and Approach

Through the course, you will come to understand the different disciplines of data analysis using hands-on examples where you actually solve real-world problems in Python.

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What You Will Learn

  • Advanced and recommend software engineering development practices.
  • How to scrape the twitter stream to collect real time data
  • Smart storing of data using advanced abstractions and Object-Oriented programming
  • Easy and practical data manipulation techniques for dealing with large volumes of data
  • Natural Language Processing tools, special designed for working with sentences and other forms of textual data
  • Predictive methods that can forecast and predict future trends based on current data
  • Data analytics techniques to tease out unseen data relationships
  • Dashboard application development to help share and monitor your progress/analysis

Authors

Video Details

ISBN 139781785880711
Course Length5 hours and 55 minutes
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