Course on Machine Learning with TensorFlow on Google Cloud [Online, 3 Months]: Enroll Now

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About the Course

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.

Skills you will gain?
  • Tensorflow
  • Machine Learning
  • Feature Engineering
  • Cloud Computing
  • Application Programming Interfaces (API)
  • Inclusive ML
  • Google Cloud Platform
  • Bigquery
  • Data Cleansing
  • Estimator
There are 5 Courses in this Specialization
  • How Google does Machine Learning
  • Launching into Machine Learning
  • Intro to TensorFlow
  • Feature Engineering
  • Art and Science of Machine Learning

To enroll in this course, click the link below.

Machine Learning with TensorFlow on Google Cloud

Note: Noticebard is associated with Coursera through an affiliate programme.

 

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