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Udemy - Learn Machine Learning 10 Projects In Finance & Health Care

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Última verificado: 24-03-2021 13:41:09

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Nome:Udemy - Learn Machine Learning 10 Projects In Finance & Health Care
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Description

Machine Learning is no longer just a niche subfield of computer science but technology giants have been using it for years – Machine learning algorithms power Walmart product recommendations, surge pricing at Uber, fraud detection at top financial institutions, content that Twitter, LinkedIn, Facebook and Instagram display on social media feeds or Google Maps. Machine learning products are being used daily, perhaps without realizing it. The future of machine learning is already here, it’s just that the machine learning career is exploding now because of smart algorithms being used everywhere from email to mobile apps to marketing campaigns. If you are in search of the most in-demand and most-exciting career domains, gearing up yourself with machine learning skills is a good move now.

In this course, we are going to provide students with knowledge of key aspects of state-of-the-art machine learning techniques. We are going to build 10 projects of the Health Care & Finance industry from scratch using the real-world dataset, here’s a sample of the projects we will be working on:

   Blood Donation Analysis
   Mortality Prediction In ICU Using ANN
   Kyphosis Disease Classification
   Suicide Rate Trend Analysis
   DNA Classification of Humans And Chimpanzee
   NYSE Stock Price Prediction
   RBI Resources Data Analysis
   E-signing of a loan based on financial history
   Prediction Of Default Of Credit Card
   Hybrid Mutual Fund Analysis

Who this course is for:

   Students who are curious in data science and machine learning

Requirements

   Basics of Machine Learning
   Healthcare & Finance knowledge is not required

Last Updated 12/2020
Video YouTube:
Categoria:Tutorials
Idioma:English  English
Total Size:3.66 GB
Informações Hash:74A18B56B1A5F6ADD85E23EC6A147626ACB6E9A3
Adicionado por:tutsnode Verified UploaderVIP
Data adicionada:2021-01-02 13:32:42
Torrent Status:Torrent Verified


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