Advanced Machine Learning with TensorFlow on Google Cloud Platform (MLTF)

 

Course Overview

This course will give you hands-on experience optimizing, deploying, and scaling a variety of production ML models. You’ll learn how to build scalable, accurate, and production-ready models for structured data, image data, time-series, and natural language text, along with recommendation systems.

Who should attend

  • 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

Prerequisites

To get the most out of this course, participants should have:

  • Knowledge of machine learning and TensorFlow to the level covered in Machine Learning on Google Cloud coursework
  • Experience coding in Python
  • Knowledge of basic statistics
  • Knowledge of SQL and cloud computing (helpful)

Course Objectives

This course teaches participants the following skills:

  • Implement the various flavors of production ML systems—static, dynamic, and continuous training; static and dynamic inference; and batch and online processing
  • Solve an ML problem by building an end-to-end pipeline, going from data exploration, preprocessing, feature engineering, model building, hyperparameter tuning, deployment, and serving
  • Develop a range of image classification models from simple linear models to high-performing convolutional neural networks (CNNs) with batch normalization, augmentation, and transfer learning
  • Forecast time-series values using CNNs, recurrent neural networks (RNNs), and LSTMs
  • Apply ML to natural language text using CNNs, RNNs, LSTMs, reusable word embeddings, and encoder-decoder generative models
  • Implement content-based, collaborative, hybrid, and neural recommendation models in TensorFlow

Prices & Delivery methods

Online Training

Duration
5 days

Classroom Training

Duration
5 days

 

Schedule

English

8 hours difference

Online Training 3 days Time zone: Eastern Daylight Time (EDT)
Online Training 3 days Time zone: Eastern Daylight Time (EDT)

9 hours difference

Online Training 3 days Time zone: Central Daylight Time (CDT)
Online Training 3 days Time zone: Central Daylight Time (CDT)

10 hours difference

Online Training 3 days Time zone: Central Standard Time (CST)
Online Training 3 days Time zone: Central Standard Time (CST)

11 hours difference

Online Training 3 days Time zone: Pacific Daylight Time (PDT)
Online Training 3 days Time zone: Pacific Daylight Time (PDT)
Instructor-led Online Training:   This computer icon in the schedule indicates that this date/time will be conducted as Instructor-Led Online Training.