Machine Learning with TensorFlow on Google Cloud Platform - Agilitics


Machine Learning with TensorFlow on Google Cloud Platform


In this 5 days of detailed training you will learn 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.

Duration: 5 days
Time: 9am to 5pm

This course teaches participants the following skills:

  • Derive insights from data using the analysis and visualization tools on Google Cloud Platform
  • Load, clean, and transform data at scale with Google Cloud Dataprep
  • Explore and Visualize data using Google Data Studio
  • Troubleshoot, optimize, and write high-performance queries
  • Practice with pre-built ML APIs for image and text understanding
  • Train classification and forecasting ML models using SQL with BQML

 

1)Getting Started with Machine Learning

2)Launching into ML

3) Optimization

4) Genralization and Sampling

5) Core tensorflow

6) Estimator API

7) Wide and Deep Models

8) Scaling tensor flow with Google Cloud AI Platform

9) Raw data and Features

10) Feature engineering

11) Regularization

12) Hyperparameter tuning

13)Custom Estimator

14) Preprocessing

Data Engineers and programmers interested in learning how to apply machine learning in practice. Anyone interested in learning how to leverage machine learning in their enterprise.

Course Duration : 5 Days

Course Fee : 3500 SGD Includes assessment

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