Login: Password:  Do not remember me


Site Info

Top Contributors:
This module

  Today: 3704
  This Month: 48847
  All Time: 669105  

  This Month: 58
  Total: 881   


1080p 2013 2014 2015 2016 2017 2018 2019 720p AC3 an BluRay BRRip Build Converter Data Edition Enterprise from Guide H264 HDRip HDTV Hindi macOS Man Multilingual New Portable Professional Studio The Theory Ultimate Video Web WEBRip Windows x264 XviD

E-Books / Video TrainingDesigning and Implementing Solutions Using Google Cloud AutoML

Designing and Implementing Solutions Using Google Cloud AutoML

Designing and Implementing Solutions Using Google Cloud AutoML
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 1 Hour 41M | 634 MB
Genre: eLearning | Language: English

Google Cloud AI offers a wide range of machine learning services. AutoML features cutting-edge technology which uses your training data to find the best model for your use case. In this course, you'll learn to build a custom machine learning model.

Most organizations want to harness the power of machine learning in order to improve their products, but they may not always have the expertise available in-house. In this course, Designing and Implementing Solutions Using Google Cloud AutoML, you'll learn how you can train custom machine learning models on your dataset with just a few clicks on the UI or a few commands on a terminal window. This course will also show how engineers and analysts can harness the power of ML for common use cases by using AutoML to build their own model, trained on their own data, without needing any specific machine learning expertise. First, you'll see an overview of the suite of machine learning services available on the Google Cloud and understand the features of each so you can make the right choice of service for your use case. You'll learn about the basic concepts underlying AutoML which uses neural architecture search and transfer learning to find the best neural network for your custom use case. Next, you'll explore AutoML's translation model, and feed in sentence pairs to the TMX format to perform German-English translation. You'll use your custom model for prediction from the UI, from the command line, and by using Python APIs. You'll also learn to understand the significance of the BLEU score to analyze the quality of your translation model. Finally, you'll use the natural language APIs that AutoML offers to build a model for sentiment analysis of reviews and work with AutoML for image classification using the AutoML Vision APIs. You'll finish up by learning the basic requirements of the data needed to train this model and develop a classifier that can identify fruits. At the end of this course, you will be very comfortable choosing the right ML API that fits your use case and using AutoML to build complex neural networks trained on your own dataset for common problems.

Buy Premium From My Links To Get Resumable Support,Max Speed & Support Me

скачать dle 12.0

Related News

Comments (0)

Add comment

Security Code: *
reload, if the code cannot be seen



«    March 2019    »