Programa de cursos integrados Machine Learning with TensorFlow on Google Cloud Platform

Iniciou em Jul 16

Programa de cursos integrados Machine Learning with TensorFlow on Google Cloud Platform

Learn ML with Google Cloud. Real-world experimentation with end-to-end ML.

Sobre esse Programa de cursos integrados

>>> By enrolling in this specialization you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at: https://qwiklabs.com/terms_of_service <<< What is machine learning, and what kinds of problems can it solve? What are the five phases of converting a candidate use case to be driven by machine learning, and why is it important that the phases not be skipped? Why are neural networks so popular now? How can you set up a supervised learning problem and find a good, generalizable solution using gradient descent and a thoughtful way of creating datasets? Learn how to write distributed machine learning models that scale in Tensorflow, scale out the training of those models. and offer high-performance predictions. Convert raw data to features in a way that allows ML to learn important characteristics from the data and bring human insight to bear on the problem. Finally, learn how to incorporate the right mix of parameters that yields accurate, generalized models and knowledge of the theory to solve specific types of ML problems. You will experiment with end-to-end ML, starting from building an ML-focused strategy and progressing into model training, optimization, and productionalization with hands-on labs using Google Cloud Platform.

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courses
5 courses

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Projetos

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Certificados

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Visão Geral dos Projetos

Cursos
Intermediate Specialization.
Some related experience required.
  1. CURSO 1

    How Google does Machine Learning

    Sessão atual: Jul 16
    Compromisso
    1 week of study, 8-10 hours/week
    Legendas
    English

    Sobre o curso

    What is machine learning, and what kinds of problems can it solve? Google thinks about machine learning slightly differently -- of being about logic, rather than just data. We talk about why such a framing is useful when thinking about building a pipe
  2. CURSO 2

    Launching into Machine Learning

    Sessão atual: Jul 16
    Legendas
    English

    Sobre o curso

    Starting from a history of machine learning, we discuss why neural networks today perform so well in a variety of problems. We then discuss how to set up a supervised learning problem and find a good solution using gradient descent. This involves c
  3. CURSO 3

    Intro to TensorFlow

    Próxima sessão: Jul 23
    Compromisso
    1 week of study, 8-10 hours/week
    Legendas
    English

    Sobre o curso

    We introduce low-level TensorFlow and work our way through the necessary concepts and APIs so as to be able to write distributed machine learning models. Given a TensorFlow model, we explain how to scale out the training of that model and offer high-perf
  4. CURSO 4

    Feature Engineering

    Próxima sessão: Jul 23
    Compromisso
    2 weeks of study, 5-7 hours per week
    Legendas
    English

    Sobre o curso

    Want to know how you can improve the accuracy of your machine learning models? What about how to find which data columns make the most useful features? Welcome to Feature Engineering on Google Cloud Platform where we will discuss the elements of good
  5. CURSO 5

    Art and Science of Machine Learning

    Sessão atual: Jul 16
    Compromisso
    3 weeks of study, 5-7 hours per week
    Legendas
    English

    Sobre o curso

    Welcome to the art and science of machine learning. In this course you will learn the essential skills of ML intuition, good judgment and experimentation to finely tune and optimize your ML models for the best performance. In this course you will le

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