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Machine Learning

Machine learning focuses on the development of computer programs that can access data and use it learn for themselves.

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Training Features

Instructor-Led Training Sessions

We believe to provide our students the Best interactive experience as part of their learning

Expert Trainers

We Constantly evaluate our trainers and only the “Best” Provides the Training

Flexible Schedule

Do not hesitate to ask… because we will work according to your calendar

Industry Specific Scenarios

Students are provided with all the Real-Time and Relevant Scenarios

e-Learning Sessions

Online training sessions are held Live and we provide students with the Training Videos

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What is Machine Learning

  • Machine learning (ML) is the study of computer algorithms that improve automatically through experience. 
  • It is seen as a subset of artificial intelligence.
  • Machine learning algorithms build a mathematical model based on sample data, known as “training data”, in order to make predictions or decisions without being explicitly programmed to do so.
  • Machine Learning is the science of getting computers to learn and act like humans do, and improve their learning over time in autonomous fashion, by feeding them data and information in the form of observations and real-world interactions.
  • Machine learning is used in internet search engines, email filters to sort out spam, websites to make personalized recommendations, banking software to detect unusual transactions, and lots of apps on our phones such as voice recognition.
  • Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. 
  • Machine learning focuses on the development of computer programs that can access data and use it learn for themselves.
  • The process of learning begins with observations or data, such as examples, direct experience, or instruction, in order to look for patterns in data and make better decisions in the future based on the examples that we provide. 
  • The primary aim is to allow the computers learn automatically without human intervention or assistance and adjust actions accordingly.

Machine Learning Course Syllabus

MACHINE LEARNING Syllabus

Introduction

Supervised Learning

Regression Techniques

Data exploration

Evaluation methods

Classification Techniques

Case Study

Unsupervised Learning

Clustering Techniques

Anomaly Detection

Dimensionality Reduction

Association Rule Learning

Hands-on on clustering

Hands-on association rule mining

Hands-on dimensionality reduction

Hands-on anomaly detection

Case Study

Reforcement Learning

Reinforcement learning vs. control design

Basic concepts in reinforcement learning

Supervised vs. unsupervised vs. reinforcement learning

Reinforcement learning workflow

Applications of Machine Learning Algorithms

Automatic Recognition of Handwritten Postal Codes

Computer-Aided Diagnosis

Computer Vision

Computer Vision

Driverless Cars

Face Recognition and Security

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MACHINE LEARNING FAQ

Being the leader in IT Software Training sector Vmoksha Trainings holds the best and inevitable place in short time

Being the leader in IT Software Training sector Vmoksha Trainings holds the best and inevitable place in short time

Being the leader in IT Software Training sector Vmoksha Trainings holds the best and inevitable place in short time

Being the leader in IT Software Training sector Vmoksha Trainings holds the best and inevitable place in short time

Being the leader in IT Software Training sector Vmoksha Trainings holds the best and inevitable place in short time

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