Machine Learning Training

In this course candidates will learn advanced and basic concepts of Machine Learning. Our machine learning online training expert faculty will be going to demonstrate challenges and solutions which belong to real-world requirements. We are covering linear regression, logistic regression, Naïve Bayes, kNN, Random forest; candidate will learn both theory and implementation of these algorithms in R and python. This course provides a comprehensive overview of each & every step that you need to learn, curriculum has been designed by highly experienced working professionals based on industry requirement.

Machine Learning Certification Training Course & Curriculum

Introduction to Machine learning

What is machine learning?
History of machine learning
Uses of machine learning
Types of machine learning

Supervised learning
Unsupervised learning
Reinforcement learning
Transfer learning
Tools for machine learning

Programming languages
Data repositories
Hierarchical databases
Software used
Basics of Python programming

Installing Python
Matrix operations
Data loading/unloading
Plotting and visualizing
Algorithms - Predicting and modeling
Statistical methods

Graph theory
Probability
Bayes theorem
Regression models
Data modeling - Linear regression

Model representation
Cost function
Gradient descent for linear regression
Data modeling - Logistic regression

Hypothesis representation
Decision boundary
Decision trees

Basics of decision trees
Uses for decision trees
Advantages and limitations
How decision trees work
Decision trees example

Create a decision tree
Requirement
Training the data
Classifiers & Support vector machines

Classifiers
Support vector machines
Linear and non linear classification
What are SVM?
Where are SVM used?
Association rules learning

What is ARL?
Where are ASL rules used?
Support, Confidence, lift and conviction
Clustering

What is clustering?
Where is clustering used?
Clustering mode
Clustering K means Model example

Preparing the data
Workbench method
Command-line method
Coded method
Basics of neural networks

Introduction to Neural Networks
Why Study Neural Networks?
Real life examples of neural network
Types of neural networks

Perception
Recurrent neural networks
Convolution neural network
Additional topics

Evaluating Model Performance
Improving Model Performance
Similarity between R and Python
Specialized Machine Learning Topics
Student Take away

Study Material
Learning stuff
Sample project for practice
Class Delivery

Live Interactive classes with expert
Delivery Methodology

We are using an experiential delivering methodology that blends theoretical concepts with hands-on practical learning to ensure a holistic understanding of the subject or course.