Nex-G Innovations

Machine learning is a method of data analysis that automates analytical model building. Using algorithms that iteratively learn from data, machine learning allows computers to find hidden insights without being explicitly programmed where to look.

It is the study of algorithms and statistical models that system uses to progressively improve their performance on a specific task for learning. This is achieved by building a mathematical model of sample data known as training data in order to make predictions or decisions on testing data without being explicitly programmed to perform the task.

Machine learning patents grew at a Compound Annual Growth Rate of thirty-four percent and had featured as the third faster-growing category of all patents granted. A forecast by International Data Corporation (IDC) indicates that spending on artificial intelligent (AI) and machine learning (ML) will grow from twelve billion dollars in 2017 to about fifty-eight billion dollars in 2021. A prediction also shows that the number of machine learning pilot and implementations will double in 2018 compared to 2017, and double again by 2020. Coupled with a lot of other fascinating insights are the latest series of machine learning market forecasts, project ions, and market estimates.

Resurging interest in machine learning is due to the same factors that have made data mining and Bayesian analysis more popular than ever. Things like growing volumes and varieties of available data, computational processing that is cheaper and more powerful, and affordable data storage. All of these things mean it's possible to quickly and automatically produce models that can analyze bigger, more complex data and deliver faster, more accurate results – even on a very large scale. And by building precise models, an organization has a better chance of identifying profitable opportunities – or avoiding unknown risks.

Machine Learning Training Objectives

• Conceptual understanding of learning applications, formulation of learning tasks as computational problems, and methods that are designed to solve these problems
• Understanding the commonalities and differences between different learning tasks and different approaches to learning
• Understanding the trade-offs in developing solutions
• Thorough understanding of rigorously evaluating the performance of learning algorithms
• Ability to manipulate, extend, and apply machine learning methods and algorithms in the context of real-world problems

Machine Learning Training Options

Training 1 - Machine Learning Python Training:

Machine Learning Using Python Training

Training 2 - Machine Learning R Programming Training:

Machine Learning Using R Programming Training

Training 3 - Machine Learning Matlab Training:

Machine Learning Using Matlab Training

Training 4 - Modeling And Optimization For Machine Learning

Modeling And Optimization For Machine Learning

Training 5 - SQL-SERVER TRAINING

SQL-SERVER TRAINING

Training 6 - Angular 8 Training

Angular 8 Training

Training 7 - ADVANCE DIPLOMA IN MACHINE LEARNING FOR HEALTHCARE

ADVANCE DIPLOMA IN MACHINE LEARNING FOR HEALTHCARE

Target Audience

Bachelor Of Technology, Bachelor Of Engineering, Bachelor Of Science, Bachelor Of Computer Application, Master Of Technology, Master Of Engineering, Master Of Science, Master Of Computer Application.

Training Customization

Currently Machine learning has varied flavors within the industry and differing adoption strategies for learning are proliferating. To reflect this we can offer a customization service to corporate customers wishing to tailor this series of learning to deliver skills to a wide range of employee roles. Complete blended learning packagers are available that may encompass our online e-learning series, instructor-led classroom technical classes delivered for both onsite and public scheduled formats, and hands-on workshops. We have already delivered Machine Learning training to reputed clients .

Training Mode

Instructor Led Class

Instructor Led Online

Onsite Corporate