The course begins with a discussion about data: how to improve data quality and perform exploratory data analysis. We describe Vertex AI AutoML and how to build, train, and deploy an ML model without writing a single line of code. You will understand the benefits of Big Query ML. We then discuss how to optimize a machine learning (ML) model and how generalization and sampling can help assess the quality of ML models for custom training.
Offert par
Google CloudÀ propos de ce cours
36 645 consultations récentes
Dates limites flexibles
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Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Niveau débutant
Approx. 17 heures pour terminer
Anglais
Sous-titres : Anglais
Ce que vous allez apprendre
Describe how to improve data quality and perform exploratory data analysis
Build and train AutoML Models using Vertex AI and BigQuery ML
Optimize and evaluate models using loss functions and performance metrics
Create repeatable and scalable training, evaluation, and test datasets
Compétences que vous acquerrez
- Tensorflow
- Bigquery
- Machine Learning
- Data Cleansing
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Niveau débutant
Approx. 17 heures pour terminer
Anglais
Sous-titres : Anglais
Offert par
Google Cloud
We help millions of organizations empower their employees, serve their customers, and build what’s next for their businesses with innovative technology created in—and for—the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success.
Programme de cours : ce que vous apprendrez dans ce cours
1 minute pour terminer
Introduction
This module provides an overview of the course and its objectives.
1 minute pour terminer
1 vidéo (Total 1 min)
4 heures pour terminer
Get to Know Your Data: Improve Data through Exploratory Data Analysis
In this module, we look at how to improve the quality of our data and how to explore our data by performing exploratory data analysis. We look at the importance of tidy data in Machine Learning and show how it impacts data quality. For example, missing values can skew our results. You will also learn the importance of exploring your data. Once we have the data tidy, you will then perform exploratory data analysis on the dataset.
4 heures pour terminer
9 vidéos (Total 57 min), 1 lecture, 3 quiz
3 heures pour terminer
Machine Learning in Practice
In this module, we will introduce some of the main types of machine learning so that you can accelerate your growth as an ML practitioner.
3 heures pour terminer
6 vidéos (Total 45 min), 1 lecture, 2 quiz
3 heures pour terminer
Training AutoML Models Using Vertex AI
In this module, we will introduce training AutoML Models using Vertex AI.
3 heures pour terminer
7 vidéos (Total 38 min), 1 lecture, 2 quiz
3 heures pour terminer
BigQuery Machine Learning: Develop ML Models Where Your Data Lives
In this module, we will introduce BigQuery ML and its capabilities.
3 heures pour terminer
8 vidéos (Total 30 min), 1 lecture, 3 quiz
1 heure pour terminer
Optimization
In this module we will walk you through how to optimize your ML models.
1 heure pour terminer
12 vidéos (Total 58 min), 1 lecture, 1 quiz
1 heure pour terminer
Generalization and Sampling
Now it’s time to answer a rather weird question: when is the most accurate ML model not the right one to pick? As we hinted at in the last module on Optimization -- simply because a model has a loss metric of 0 for your training dataset does not mean it will perform well on new data in the real world. You will learn how to create repeatable training, evaluation, and test datasets and establish performance benchmarks.
1 heure pour terminer
5 vidéos (Total 28 min), 1 lecture, 1 quiz
2 heures pour terminer
Summary
This module is a summary of the Launching into Machine Learning course
2 heures pour terminer
4 lectures
Avis
- 5 stars69,34 %
- 4 stars23,79 %
- 3 stars5,01 %
- 2 stars1,19 %
- 1 star0,64 %
Meilleurs avis pour LAUNCHING INTO MACHINE LEARNING
par AK25 août 2018
Very good course for beginners! -1 star because I find labs to be less informational and practical and course to be more theoretical that practical!
par PT25 juin 2018
Overall it was great, and very instructive. However, the Short History of ML was a little bit confusing with too many unexplained words and too many details too early.
par AM13 juil. 2018
Great presenter. High energy engaging. The material is more difficult and to develop intuition of why the sampling needs to result in constant RMSE didn't come across.
par SK5 mai 2019
This course is very helpful to understand the machine learning concepts of various modals, splitting of the data and even training the model for benchmark.
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