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Machine Learning in the Enterprise

Machine Learning on Google Cloud,

This course takes a real-world approach to the ML Workflow through a case study. An ML team faces several ML business requirements and use cases. The team must understand the tools required for data management and governance and consider the best approach for data preprocessing. The team is presented with three options to build ML models for two use cases. The course explains why they would use AutoML, BigQuery ML, or custom training to achieve their objectives.
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Rating 4.3 based on 85 ratings
Length 4 weeks
Effort 3 weeks of study, 5-7 hours per week
Starts Jun 26 (45 weeks ago)
Cost $49
From Google Cloud via Coursera
Instructor Google Cloud Training
Download Videos On all desktop and mobile devices
Language English
Subjects Data Science Programming IT & Networking
Tags Data Science Machine Learning Cloud Computing Information Technology

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What people are saying

best course

best course in the specialization!!!

The best course ever to give you the glimpse of the whole ML land - what is ML?

This is an extensive course where you learn some handy techniques like embedding which I believe will be very handy for many applications Thank you Google and Coursera Best course in this specialization.

The best course of the specialization.

This is one of the best courses in this specilization, as it goes deeper in the internals of ML and Neural Networks.

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machine learning

Its one of the best course for machine learning Labs were had less quality than in previous weeks.

Excelente Loved the breadth and depth of machine learning topics in this course.

good Great course for understanding in and out of Machine learning model.

Now I am starting "Advanced Machine Learning with TensorFlow on Google Cloud Platform Specialization".

Especially if you don't have a machine learning background.

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custom estimators

Specifically the last modules with custom estimators and the ability to create estimators straight from Keras!

Also, it presents two important features such as Embedding (creating sparse tensors from features) and Custom Estimators, which is the first step to get into advanced topics such as implementing new estimators from Research Papers.I've really leveraged from this course a lot.

Finally the course also opens the door to custom estimators, keeping you interested for the next courses.

If customer estimator was explained in the earlier courses, many other experiments with our own custom estimators could have been tried.

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Careers

An overview of related careers and their average salaries in the US. Bars indicate income percentile.

Hitting Coach @ ML LEVEL $49k

Chef Team $52k

Special Educator for SEIT Cases $56k

Policy Team $63k

Machine Learning Scientist, ML Platform $66k

Admin. Team $67k

Team Marketing $75k

Team Lead 1 3 $101k

SAN Team $102k

Manufacturing Engineer - ML ME Measurement $103k

A/P TEAM LEADER $118k

Team Project $151k

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Rating 4.3 based on 85 ratings
Length 4 weeks
Effort 3 weeks of study, 5-7 hours per week
Starts Jun 26 (45 weeks ago)
Cost $49
From Google Cloud via Coursera
Instructor Google Cloud Training
Download Videos On all desktop and mobile devices
Language English
Subjects Data Science Programming IT & Networking
Tags Data Science Machine Learning Cloud Computing Information Technology

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