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Course

Online Advanced Machine Learning with TensorFlow on Google Cloud Platform

50.1%

Course Objective

This series of courses 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.

Audience

  • Data Engineers and programmers interested in learning how to apply machine learning in practice.
  • Anyone interested in learning how to build and operationalize TensorFlow models

Prerequisites

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

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

COURSE START DATES

Start Date Time DaysLocation
18/05/202010.00 - 17.00Mon to FriBrentford
20/07/202010.00 - 17.00Mon to FriBrentford
21/09/202010.00 - 17.00Mon to FriBrentford
23/11/202010.00 - 17.00Mon to FriBrentford

Course Content

End-to-end ML with TensorFlow on Google Cloud Platform

  • Batch prediction
  • Online Prediction
  • Batching up online predictions
  • Handling fault tolerance in production ML systems

Production ML Systems

  • Compare static vs. dynamic training and inference
  • Manage model dependencies
  • Set up distributed training for fault tolerance, replication, and more
  • Export models for portability

Image Understanding with TensorFlow on Google Cloud Platform

  • Classify images using deep learning
  • Implement convolutional neural networks
  • Improve the model by augmentation, batch normalization, etc.
  • Leverage transfer learning

Sequence Models for Time Series and Natural Language Processing

  • Predict future values of a time-series
  • Classify free form text
  • Address time-series and text problems with recurrent neural networks
  • Choose between RNNs/LSTMs and simpler models
  • Train and reuse word embeddings in text problems

Recommendation Systems with TensorFlow on Google Cloud Platform

  • Devise a content-based recommendation engine
  • Implement a collaborative filtering recommendation engine
  • Build a hybrid recommendation engine with user and content embeddings

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Duration 5 Days
Price £3,990.00 £1,990.00

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