Machine Learning Course by Google: Machine Learning With TensorFlow On Google Cloud Platform Specialization

125
Machine-Learning-Definition_Basic_Introduction
Machine-Learning-Definition_Basic_Introduction

[editorskit display=”wordcount” before=”Reading Time: ” after=” min”]

Machine Learning Course by Google: Google Machine Learning Coursera Course

Here we are going to discuss some of the popular Machine Learning Courses by Google. These Machine Learning Courses by Google can be very helpful to enhance your career in Data Analytics, Machine Learning and Artificial Intelligence. Before Diving deep into the specific Machine Learning Courses by Google, let’s first understand the basic concept of Machine Learning and how it functions.

Charles Green, the Director of Thought Leadership at Belatrix Software states:

“It’s a huge challenge to find data scientists, people with machine learning experience, or people with the skills to analyse and use the data, as well as those who can create the algorithms required for machine learning. Secondly, while the technology is still emerging, there are many ongoing developments. It’s clear that AI is a long way from how we might imagine it.”

This statement, in one way, indicates a path and scope towards becoming an expert in the field of Machine Learning. You must first understand basic classical statistics to build and program intelligent machines while computer programming is another indispensable part of Machine Learning you can’t avoid.

Thus, Machine Learning can be defined as the systems with more intelligence and with the ability to learn automatically and improve continuously from experiences rather than being programmed explicitly. The most important feature of Machine Learning is the “Self-learning” ability of the system. This “self-learning” behaviour in Machine Learning is achieved through the application of statistical modelling to detect pattern and improve performance for themselves without explicit programming. Machine Learning can adapt and modify its behaviour by reacting to errors while traditional programming can be highly susceptible to such errors. There are many more statistical-based algorithms for Machine Learning and choosing the right algorithm (or combination of algorithms) for your job is always challenging for anyone working in this field.

Machine Learning has mainly three steps: Data -> Model -> Action.

Machine Learning Courses By Google: Machine Learning With TensorFlow On Google Cloud Platform Specialization

The first Google Machine Learning Coursera course I would like to discuss is Machine Learning with TensorFlow on Google Cloud Platform Specialization, one the best specialization Machine Learning Courses by Google. This Machine Learning Google Coursera Course is offered by Google Cloud Training unit and you can learn Machine Learning (ML) with Google Cloud by real world experimentation with end-to-end Machine Learning (ML). The five-course series, Machine Learning with TensorFlow on Google Cloud Platform Specialization, a Machine Learning Courses by Google can be enrolled for free we can get 7-days full access free trial.

Some of the major skills that you can learn from this Free Machine Learning Courses by Google are:

  • TensorFlow,
  • Machine Learning,
  • Feature Engineering,
  • Cloud Computing,
  • Application Programming Interfaces (API),
  • Inclusive Machine Learning (ML),
  • Google Cloud Platform,
  • Big-query,
  • Data Cleansing,
  • Estimator

Course Description: Machine Learning with TensorFlow on Google Cloud Platform Specialization

What is machine learning and what types of problems can it solve? What are the five steps of converting a candidate use case to operate by machine learning, and why is it important that the steps should not be skipped? Why are Neural Networks popular now? You can learn to write scalable distributed machine learning models in Tensorflow, measure the training of those models and also offer high-performance predictions. You can transform raw data in ways that allow MLs to learn key features from data and bring human insights to bear on the problem. Finally, you shall learn to incorporate the right mix of parameters that give knowledge of precise, generalized models and theory to solve specific types of ML problems. You’ll get to experiment with hands-on labs using the Google Cloud Platform to create model-focused strategies and end-to-end MLs starting with advances in model training, optimization, and productization.

This expertise incorporates hands-on labs using Google’s popular Qwiklabs platform. These hands-on components will let you apply the skills learned in video lectures. The projects will cover topics such as Google Cloud Platform products, used and configured within Qwiklabs. You can expect to gain practical hands-on experience with the concepts stated throughout the module.

How Google Machine Learning Coursera Courses Specialization Work?

First take a course or course

The Machine Learning with TensorFlow on Google Cloud Platform Specialization, a Machine Learning Courses by Google Specialization offered by Coursera is a series of courses that helps you master specific skills in ML. To get started, you can enroll directly in the specialization course, or review its individual courses and choose the one you want to start with. When you subscribe to a course that is part of the Machine Learning Courses by Google specialization offered by Coursera, you automatically get the full specialization. It is okay to complete only one course – you can stop your course or terminate your membership at any time. Go to your learner dashboard to track your course enrollment and your progress.

Machine Learning with TensorFlow on Google Cloud Platform Specialization: Hands-on Project

Every Google Machine Learning Coursera specialization involves a hands-on project. To complete Machine Learning with TensorFlow on Google Cloud Platform Specialization and earn your certificate you will need to complete the specified project successfully. If the Machine Learning Courses by Google specialization includes a separate hands-on project, you must complete each of the other courses before starting it.

How to Earn a Certificate on Machine Learning with TensorFlow on Google Cloud Platform Specialization

Coursera_Sample_Certificate
Coursera Sample Certificate

Once you complete each course and also complete the hands-on projects in Machine Learning with TensorFlow on Google Cloud Platform Specialization, you will earn a certificate, which you can share with prospective employers and your professional network like linkedin. You can share your course certificate on printed resumes, CVs, or other documents in the Certification section of your LinkedIn profile.

There are five courses in Machine Learning with TensorFlow on Google Cloud Platform Specialization that you need to complete for this machine Learning Courses by Google Cloud Training.

Read more about specific Machine Learning Course by Google: Machine Learning with TensorFlow on Google Cloud Platform Specialization.

Course 1: How Google Does Machine Learning (Machine Learning Course by Google)

Course 2: Launching Into Machine Learning (Machine Learning Course by Google)

Course 3: Intro To Tensorflow (Machine Learning Course by Google)

Course 4: Feature Engineering (Machine Learning Course by Google)

Course 5: Art And Science Of Machine Learning (Machine Learning Course by Google)

LEAVE A REPLY

Please enter your comment!
Please enter your name here