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[Udemy] AWS Machine Learning, AI, SageMaker - With Python (2017)

Тема в разделе "Udemy.com", создана пользователем Toretto, 12 ноя 2018.

  1. Toretto

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    [Udemy] AWS Machine Learning, AI, SageMaker - With Python (2017)

    *** NEW: SageMaker Lectures are On-line now. XGBoost - Gradient Boosted Tree algorithm in-depth with hands-on. XGBoost has won several competitions and is a very popular Regression and Classification Algorithm, Factorization Machine based Recommender Systems and PCA for dimensionality reduction ***

    There are several courses on Machine Learning and AI. What is special about this course?

    Here are the top reasons:


    1. Cloud based machine learning keeps you focused on the current best practices.
    2. In this course, you will Learn most useful algorithms. Don’t waste your time sifting through mountains of techniques that are in the wild
    3. Cloud based service is very easy to integrate with your application and has support for wide variety of programming languages.
    4. Whether you have small data or big data, elastic nature of the AWS cloud allows you to handle them all.
    5. There is also No upfront cost or commitment – Pay only for what you need and use
    In this course, you will learn AI and Machine Learning in three different ways:

    AWS Machine Learning

    AWS Machine Learning Service is designed for complete beginners.

    You will learn three popular easy to understand linear algorithms from the ground-up

    You will gain hands-on knowledge on complete lifecycle – from model development, measuring quality, tuning, and integration with your application

    AWS SageMaker

    The next service is AWS SageMaker.

    If you are comfortable coding in Python, SageMaker service is for you.

    You will learn how to deploy your own Jupyter Notebook instance on the AWS Cloud.

    You will gain hands-on model development experience on very powerful and popular machine learning algorithms like


    • XGBoost – a gradient boosted tree algorithm that has won several competitions,
    • Recurrent Neural Networks for Time Series forecasting,
    • Factorization Machines for high dimensional sparse datasets like Click Stream data
    • Neural Network based Image Classifiers,
    • Dimensionality reduction with Principal Component Analysis
    • and much more
    Application Services

    In Application Services section of this course,

    You will learn about a set of pre-trained services that you can directly integrate with your application.

    You will gain hands-on experience in ready-to-use Vision service for image and video analysis, Conversation chatbots and Language Services for text translation, Speech recognition, and text to speech and more

    I am looking forward to seeing you in the course.

    ПРОДАЖНИК
    udemy.com/aws-machine-learning-a-complete-guide-with-python/


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