Description

If you’re amazed by the machine learning hype and want to know what it can do for your enterprise, without the technobabble, this Machine Learning for Business Professionals course is for you. In this class, learn what machine learning is, how to translate business problems into machine learning use cases, how to vet those use cases for feasibility and impact, how to discover unexpected use cases, how to carry a machine learning project through its various phases, and how to pursue machine learning and artificial intelligence responsibly and ethically.

 

Radiant Techlearning offers Machine Learning for Business Professionals training program in Classroom & Virtual Instructor Led / Online mode.

 

Duration 1 Day

 

Learning Objectives

  • Machine Learning

 

 

Pre-requisites

Audience Profile:

Traditional enterprise business decision makers

Course Content

This course is designed to be an introduction to machine learning for non-technical business professionals. Machine learning is in high demand in the industry and it is concerned that in order to use machine learning in business, technical background is a must. For reasons that are covered in this course, that’s not the case. In practice, your business knowledge is far more important than your ability to build an ML model from scratch. By the end of this course, professionals be able to:

  • Formulate machine learning solutions to real-world problems
  • Identify whether the data you have is sufficient for ML
  • Carry a project through various ML phases including training, evaluation, and deployment
  • Perform AI responsibly and avoid reinforcing existing bias
  • Discover ML use cases
  • Be successful at ML you’ll need a desktop web browser to run this course’s interactive labs via Qwiklabs and Google Cloud Platform.

 

Introduction

  • This module reviews the learning objectives for the course and introduces technology that will be important for completing labs.

 

What is Machine Learning?

  • This module defines what machine learning is, provides examples of how businesses are using it, contextualizes recent advances in machine learning, and reviews how artificial intelligence raises important ethical questions.

 

Employing ML

  • This module reviews how to do machine learning, including how to label data, train and evaluate models and avoid reinforcing bias.

 

Discovering ML Use Cases

  • This module reviews broad categories of ML use cases in order to jump start your ideation.

 

How to be successful at ML

  • This module reviews what your business must do in order to be successful at ML, including how to acquire data, how to appropriately govern that data, and how to create a culture of innovation.

 

Summary

  • This module reviews the content in the course.

FAQs

Q: What are the three stages of building a model in machine learning?

 

A: Three stages of building a model are:-

  • Model Building: In this stage user have to choose a suitable algorithm for the model and train it according to the requirement
  • Model Testing: In this stage user have to check the accuracy of the model through the test data
  • Applying the Model: In this stage user have to make the required changes after testing and use the final model for real-time projects

Here, it’s crucial to remember that once in a while, the model needs to be checked to make sure it’s working correctly. It should be modified to make sure that it is up-to-date.

 

Q: What do you mean by Overfitting and how you can avoid it?

 

A: Overfitting is a condition which occurs when a model learns the training set too well, taking up random fluctuations in the training data as concepts. These impact the model’s great ability to generalize and don’t apply to new data.

When a model is given the training data, it shows 100 % accuracy—technically a slight loss. But, when user use the test data, there may be a chance of an error and low efficiency. This condition is known as overfitting.

There are various ways of avoiding overfitting, such as:

  • Regularization which involves a cost term for the features involved with the objective function
  • Making a simple model. With lesser amount of variables and parameters, the variance can be reduced
  • Cross-validation methods such as k-folds can also be used
  • If there are some model parameters which are likely to cause overfitting, techniques for regularization like LASSO can be used that penalize these parameters

 

Q: What are the business benefits of machine learning?

 

A: Some of the business benefits by machine learning are

listed below:-

  • Generally it simplifies Product Marketing and Assists in Accurate Sales Forecasts.
  • Facilitates Accurate Medical Predictions and Diagnoses.
  • Simplifies Time-Intensive Documentation in Data Entry.
  • Improves Precision of Models and financial rules.
  • Easy Spam Detection.

 

Q: What is the meaning of selection bias?

 

  • A: It is a statistical error which mainly causes a bias in the sampling portion of an experiment.
  • The error generally causes one sampling group to be selected more often than other groups included in the experiment.
  • Selection bias possibly may also produce an inaccurate result if the selection bias is not identified.

 

Q: Where is Radiant Techlearning Located?

 

A: Radiant Techlearning is headquartered in Electronic city and technology hub of Northern India, Noida, which is surrounded by several large multinational, medium and small Software companies. We have our offices located all across the country and partners across the globe.

 

Q: What is the schedule of the training program?

 

A: Radiant Techlearning offers training program on the weekday, weekend and a combination of weekdays and weekends. You can always choose the schedule that best suits to your need.

 

Q: What kind of projects are included as a part of training?

 

A: The learners will be enthralled as we engage them the real world and industry Oriented projects during the training program. These projects will improve your skills and knowledge and you will gain better experience. These real time projects, they will help you a lot in your future tasks and assignments.

 

Q: Where is Radiant Techlearning Located?

 

A: Radiant Techlearning is headquartered in Electronic city and technology hub of Northern India, Noida, which is surrounded by several large multinational, medium and small Software companies. We have our offices located all across the country and partners across the globe.

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