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Machine Learning

Course Objectives

This Level focuses on building all the important and popular machine learning Models and Algorithms that provide you the basis of working as a professional Data Scientist. You will learn and work hands-on to create your models based on different advanced techniques as well as learn how to evaluate and enhance the model’s efficiencies and accuracy. .

Course Overview


Machine Learning
Machine learning is a method of data analysis that automates analytical model building. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention. We are using machine learning in our daily life even without knowing it such as Google Maps, Google assistant, Alexa, etc. Machine Learning provides smart alternatives to analyzing vast volumes of data. By developing fast and efficient algorithms and data-driven models for real-time processing of data, Machine Learning can produce accurate results and analysis. In classic terms, machine learning is a type of artificial intelligence that enables self-learning from data and then applies that learning without the need for human intervention.

ANNEX Training Institute is Leading Training Institute in Abu Dhabi UAE, which we focused on Providing Quality Educating and Training program. ANNEX is Accredited by Abu Dhabi Center for Technical Vocational Education & Training (ACTVET) With Specialization in Computer Software, Standardized Test, Language and Management Program.

Applications of Machine Learning

Automatic Language Translation
Medical Diagnosis
Stock Market Trading
Online Fraud Detection
Virtual Personal Assistant
Email Spam and Malware filtering
Self-Driving Cars
Product recommendations
Traffic Prediction
Speech recognition
Image Recognition

Section 1: Introduction to ML

What is ML?
Why ML?
Introduction to Supervised ML
Instruction to unsupervised ML

Section 2: Supervised Learning

Introduction
Linear Regression
Multiple regression
Categorical Independent variable
Root mean square error
Mean absolute error
Regression – Pros and cons
Hands On
Logistic Regression
Precision recall
Hands on

Section 3: Ensemble Techniques

Decision Trees
Pruning
Ensemble Intro
Bagging, Boosting
Hands on

Section 4: Feature Selection and cross validation

Introduction
Feature Engineering
K Cross Validation

Section 5: Unsupervised Learning

Introduction
Clustering
K-Means Clustering
Applications
Advantages and Disadvantages
Hierarchical Clustering
Principal Component Analysis

Course Duration:

Course Duration is Minimum 40 Hours.

Take the right step,
do the big things.

100+
Courses
60+
Experienced Trainers
40
Countries
100%
Satisfied Students
Flexible Timing

The Flexible Working Hours
Policy allows students of a
any category.

Individual Attention

We are giving individual
learning and individual
attention of every students.

Affordable Fees

Our fee structure is very less
compare to other training
centre.

Experienced Trainers

Authorized Trainers are
appropriately qualified,
skilled in teaching.

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