In this course, you will learn how to develop ML (Machine Learning) models to resolve business issues with the help of Google Cloud technologies which are widely used to design ML models.
DurationIn this course, you will learn how to develop ML (Machine Learning) models to resolve business issues with the help of Google Cloud technologies which are widely used to design ML models.
You will also learn the process of framing ML problems while designing ML models. You will also be able to design and develop solutions for ML Architect, as well. You will learn about how to process and prepare data to configure, enhance and troubleshoot ML solutions.
Through the subject matter of this course, you will learn about the techniques of processing data, including the deployment of Simple Linear, Multiple Linear, and Polynomial Regression. You will be able to configure the process of clustering data.
Here, you will also earn adequate knowledge and skills to start working on NLP (Natural Language Processing) and Deep Learning. You will also learn about the process of model boosting and model selection.
Prerequisites
There is no particular prerequisite mentioned to get enrolled in this course.
It is ideal if you have prior experience of working with ML, but not required.
It is expected that you are familiar with the ML Data model and ML Architect.
It would be better if you have the fundamental knowledge about Data Clustering and NLP (Natural Language Processing)
It is also expected that you are familiar with supervised learning and unsupervised learning.
What will you gain after this course
You can develop ML models to train the ML architecture with a particular set of data.
You will learn the details about Data Clustering
You will be able to work on ML solutions
You will earn adequate knowledge and skills on Deep Learning and NLP
You will also be able to develop ML solutions using different types of the data regression model
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