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Machine Learning Web Applications - Advanced

  I have always wanted to develop a complete Machine learning application where I would have a UI to feed in some inputs and the Machine ...
 Machine Learning Web Applications - Advanced


4.5 (11 ratings)
98 students enrolled
Created by Manuel Amunategui
Last updated 1/2019 
 
What you'll learn
  • Learn how to extend machine learning into rich and complex web applications
  • Learn how to extend Flask with Machine Learning
  • Learn how to create rich UI to interact with complex machine learning algorithms
  • Learn how to create and use Rest APIs
  • Learn to use cloud providers: Google Cloud and PythonAnywhere
Requirements
  • Knowledge of Python, how to pip install, how to use Numpys and Pandas is required
  • Basic knowledge of HTML, CSS and web forms is expected
  • Some knowledge, even if its just a light introduction to machine learning would be helpful
Description 
 
In this class, we will take machine learning concepts and models and extend them into fully interactive web applications for the world to enjoy. No more do they need to know statistics, python, linear regression or Tableau to enjoy your work. Anybody with an Internet connection should be able to interact with your research, findings and intelligence using typical and ubiquitous web controls.
We will work on 4 case-studies. We will start with a linear regression to predict life expectancy. We will extend it into an interactive web application to query how many more years you have to live (yikes). We will create a wine designer using GBM. We will create an HTML5 canvas control to draw digits and use a Tensorflow model to predict them. Finally we will predict the stock market using XGBoost and feed the results through a REST API control.
Two of the case studies will be deployed onto cloud providers: Google Cloud and PythonAnywhere
This class will teach you one of the most important skills a data scientist needs to learn today.  Most data scientists know how to load and transform data, they also know how to run linear regressions but few know how to work with clients and deliver ML tools they can use. This skill will boost your career and make you a fully balanced, self-sufficient ML tool creator that can handle any stage of the delivery pipeline. Are you ready?
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